The ultimate goal of my research is to uncover subtle acts of influence in strategic interactions across genders and any ensuing impacts on their performance evaluations and outcomes. Hence, I collect novel data sets from strategic interaction settings of inter-collegiate debate tournaments & MBA negotiation exchanges using text mining, argument mining and micro-econometric techniques. In another research strand, I borrow tools from banking contagion models to theoretically understand the impact of homophily in team innovation decisions.
You can read more in detail my Research Statement here. Below are the summary abstracts of my research papers.
The (Great) Persuasion Divide? Gender Disparities in Debate Speeches & Evaluations
[paper available upon request] [slides]
Upcoming: AGEW Australian Gender Economic Workshop (cyberspace), RES Annual Conference (cyberspace), AYEW Applied Young Economist Webinar (cyberspace), SOLE Society of Labor Economists Annual Conference (cyberspace), Spring Meeting of Young Economists 2021 (Bologna),
Economics of Gender & the Workplace Workshop (Rotterdam, cancelled), Science of Diversity & Inclusion Convening (Berkeley, cancelled)
Presented at: : Minerva Lab on Diversity & Gender Inequality (cyberspace), YSI – INET Plenary – “New Approaches to Old Questions : Current Debates in Feminist Economics” (cyberspace), YSI – INET Plenary – “Developing Countries: Challenges to Face Inequality “ (cyberspace), VfS Annual Conference – Gender Economics (cyberspace), Econometric Society World Congress (ESWC) (cyberspace), EALE SOLE AASLE World Conference 2020 (cyberspace), RGS Doctoral Conference in Economics (Dortmund), ESE Female Network Seminar (cyberspace), WUDC Gender Inclusion Panel Discussion (Bangkok), CBS Behavioral Working Group Seminar (New York), 2019 Econometric Society Winter Meeting (ESWM) (Rotterdam), Natural Language, Dialog and Speech Symposium of the New York Academy of Sciences (New York), CBS Chazen Institute Research Scholar Seminar (New York), Data Science Institute Poster Session (New York), Zurich Text As Data Workshop (Zurich), International Association of Applied Econometrics 2019 (Nicosia), TIBER Symposium on Psychology & Economics (Tilburg), Eastern European Machine Learning Summer School 2019 (Bucharest), Data Science Summer School 2018 (Paris), EUR Brownbag Seminar 2019, EUR Diversity Research Seminar 2018
Do men and women persuade differently? Are they evaluated differently? Using a data set of 1517 speech transcripts, evaluation scores and demographic data from prestigious university debate tournaments, I investigate spoken verbal tactics across genders and any ensuing impacts on their performance evaluations. On average, female debaters use less hierarchical, more personal and disclosing style, and more hedges and fillers in their speeches. In terms of evaluation, speeches given by women receive 0.16 standard deviation lower score compared to those given by men. Controlling for debate room and judge panel characteristics, speeches given by women with analytical style and fillers received harsher punishment, whereas personal pronouns and positive emotional tone are associated with higher scores. At debate-room level, except for fillers, other effects become statistically insignificant. These findings suggest that, linguistic-wise, women receive lower scores mainly because their speeches contain more score-reducing and less score-enhancing features, rather than gender-specific evaluation standards.
First Impression is the Last Impression? Acoustic-Prosodic Cues to Persuasiveness in Competitive Debate Speeches (with Sarah Ita Levitan, David Lupea and Julia Hirschberg)
1st Prize STAR Presentation Award, NYAS NDS2020 (cyberspace)
Presented at: STAR Talk @ Natural Language, Dialogue and Speech Symposium of the New York Academy of Sciences (cyberspace)
Using a data set of over 1800 audio segments of first and last minutes of debate tournament speeches, their evaluation scores and demographic data, we investigate gender disparity in acoustic-prosodic features and how they correlate with evaluations of persuasiveness. Debate tournaments provide a useful means of systematically answering these questions because they include these four components: (i) a diverse pool of intrinsically motivated professional debaters; (ii) exogenously assigned speaking position, topic and opponents; (iii) transparent scoring criteria, based purely on comparative argumentation strength; and (iv) accountable, selective panels of judges. We analyze the acoustic-prosodic correlates of persuasiveness (i.e. pitch, intensity, harmonic-to-noise ratio (HNR), jitter, shimmer and speaking rate), taking into account individual traits (e.g: gender, native language, institution ranking, study major), to explore the existence and magnitude of discriminatory evaluation standards across social groups. This work contributes a large-scale analysis of acoustic-prosodic cues in a strategically relevant context, and discusses how demographic characteristics of speakers influence judges’ perception of persuasive argumentative speeches.
Do Women Give Up Competing (Against Men) Too Early? Evidence from World & European Debate Tournaments
Using an 11-year panel data set of 105 553 speech evaluation scores and gender composition of 13 243 debate rooms in World & European universities debate tournaments, this research exploits the regression discontinuity design of debate tournaments & exogenous assignment of opponents in debate tournament rounds to investigate whether women give up competing too early, especially when faced with more men in the debate room. Across the preliminary rounds, women score significantly lower than men, especially if faced with stronger teams at the start. Furthermore, women, but not men, who fail to make it to the elimination rounds and/or top 50 best speakers, are less likely to compete again the following year. This gender difference in persuasion competitiveness may help to explain the persistent lack of women in high-ranked positions.
Gender Differences in Negotiation Tactics -A Text Mining Approach (with Malia Mason)
Building on recent work using text as data to study politeness and receptiveness in negotiations, we employ dictionary-based text mining techniques on a set of 1000 e-mail & 180 face-to-face negotiation exchanges among MBA professionals to uncover gender disparities in negotiation tactics. Preliminary findings in the face-to-face negotiation exchanges show that women across the board use significantly more polite language, indirect questions and hedges, as compared to men. By correlating these linguistic features to individual’s professional industry, personality measures and dyad-specific negotiation outcomes, we discuss the effectiveness of negotiation strategies for each gender, in both integrative and distributive negotiation contexts.
Two of a Kind Try Together? The Impact of Homophily on Innovation Decisions in Teams (with Josse Delfgaauw)
Presented at: 33rd European Economic Association Annual Meeting (Cologne), 3rd Lectures on Organizational Economics & Human Resources (Cologne), TI PhD Seminar, EUR Brownbag Seminar
The tendency to disproportionately interact with similar others (i.e. homophily) is a ubiquitous social phenomenon. While it is commonly hypothesized that homophily hampers group creativity and innovation, empirical findings are mixed. This research examines the impact of homophily on innovation in teams, in a simple setting where agents decide whether or not to implement a project that embodies strategic complementarity. Agents receive conditionally correlated private signals about the innovation quality, where homophily is the degree of correlation between the signals. Our key result is as follows: When agents share information truthfully, homophily reduces the probability of implementation; whereas the opposite occurs without information sharing. Given these effects, we discuss an alternative interpretation of homophily as correlated benefits and several extensions in correlation neglect, information collection behavior and strategic communication within the organizational context.