Dissertation Defense: “Essays on the Economics of Extremism in the United States” Danny Klinenberg
Speaker
Danny Klinenberg, University of California, Santa Barbara
Biography
Danny is a third-year PhD student studying Economics at UCSB. He graduated from Cal Poly San Luis Obispo with a BS and MS in Quantitative Economics in 2018.
Event Details
Join us to hear Danny’s dissertation defense. He will be defending his dissertation, “Essays on the Economics of Extremism in the United States." To access a copy of the dissertation, you must have an active UCSB NetID and password.
Abstract
Essays on the Economics of Extremism in the United States by Daniel Klinenberg
This dissertation consists of two essays studying extremism in the United States using economic tools
and theory and one essay extending a well-known econometric method.
In the first chapter, I study how domestic extremist organizations in the United States attract new
members. Such organizations have become a significant threat to Western democracies, with some
groups attracting tens of thousands of members. I study the impact of three tactics membership
discounts, armed events, and advertisements on national recruitment by the Oath Keepers,
Americas largest paramilitary organization. Using a synthetic control framework, I find that
discounts cause new member signups to increase by 144% and armed events by 170%; however,
advertisements decrease it. Finally, I fail to find strong evidence that economic inequality drives
the inflow of new members during any tactic.
In Chapter 2, I study the efficacy of social media policy designed to curb extremist activity. While
governments deliberate on how to regulate, some social media companies have removed creators of
offensive content – deplatforming. I estimate the effects of deplatforming on revenue and
viewership, using variations in the timing of removals across two video-streaming companies
YouTube, and its far-right competitor, Bitchute. Being deplatformed on YouTube results in a 30%
increase in weekly Bitcoin revenue and a 50% increase in viewership on Bitchute. This increase in
Bitchute activity is less than that on YouTube, meaning that deplatforming works in decreasing a
content creator’s overall views and revenue.
Finally, Chapter 3 extends the synthetic control methodology to account for more scenarios.
Synthetic control methods are a popular tool for measuring the effects of pol- icy interventions on a
single treated unit. In practice, researchers create a counterfactual using a linear combination of
untreated units that closely mimic the treated unit. Oftentimes, creating a synthetic control is not
possible due to untreated units’ dynamic characteristics such as integrated processes or a time
varying relationship. These are cases in which viewing the counterfactual estimation problem as a
cross-sectional one fails. In this paper, I investigate a new approach to estimate the synthetic control
counterfactual incorporating time varying parameters to handle such situations. This is done using a
state space framework and Bayesian shrinkage. The dynamics allow for a closer pre-treatment fit
leading to a more accurate counterfactual estimate. Monte Carlo simulations are performed
showcasing the usefulness of the proposed model in a synthetic control setting. I then compare the
proposed model to existing approaches in a classic synthetic control case study.
