Description:

Speaker: Andrew Wooders "The Impacts of Social Activism on Discrimination"

Speaker: Seung Hyeong Lee "Guidance-Driven Heterogeneity and Forecast Dispersion"

Abstract for "The Impacts of Social Activism on Discrimination": 

“We study the effects of social activism on racial discrimination and social attitudes, and how these effects are manifested in market outcomes. We study three distinct social activism events that occurred in response to police brutality against African Americans in the United States -- the Philando Castile shooting, Colin Kaepernick kneeling during the national anthem, and the George Floyd protest. Following over 1.2 million transactions across over 10 years in the secondary market for baseball cards, we find differential changes in market prices between cards of black and white players following each of these social justice events. We exploit novel institutional details combined with a difference-in-difference framework to identify and quantify these market trends as changes in racial attitudes. For example, we find that the George Floyd protests in May 2020 resulted in an average 8.3\% increase in prices of black cards, which we attribute to changes in racial attitudes and perceptions in favor of African Americans. Our results both identify and quantify the impact of social activism on racial discrimination in markets, and provide novel insights into the role of social activism in bringing forth important behavioral changes in individuals, markets, and society."

Abstract for "Guidance-Driven Heterogeneity and Forecast Dispersion": 

"We analyze how equity analysts systematically utilize firms' earnings guidance and announcements when making forecasts. Approximately 35% and 52% of analysts' (sums of) quarterly EPS forecasts deviate by less than 1 cent and 2 cents, respectively, from their corresponding benchmarks implied by annual guidance and announced quarterly earnings. We identify two channels that affect forecast dispersion: how closely forecasts align with the benchmark and the number of `free forecasts' analysts have to match the annual guidance. We create measures to capture these channels and empirically test their relationship with forecast dispersion. Our long-short portfolio generated from two measures yields a monthly abnormal return of 1.08%. The findings suggest researchers should be cautious when interpreting dispersion across analysts' forecasts as a measure of heterogeneous beliefs or risk."