Welcome! I am a postdoctoral researcher at BI Norwegian Business School, currently applying advanced machine learning methods to large-scale administrative data to derive key labor market insights.
I greatly enjoy economic and statistical consulting in a wide range of application, particularly those combining advanced statistical modeling problems with complex societal questions, and I am open to discussing new projects.
My Research
My academic work focuses on labor economics, econometrics (especially robust Bayesian methods and machine learning methods), and labor history, although my research interests extend beyond these fields. I am particularly interested in worker voice: the influence that workers may exercise in a firm’s decision-making, such as through a union; I also study how worker voice may interact with technological changes such as the rise of remote work and digital surveillance by employers.
I have been a research assistant for Ina Ganguli and Richard Freeman studying technology, the future of work, and the effects of COVID-19.
Prior to graduate school, I worked at the Stanford METRICS institute, using Bayesian methods to study the reproducibility of medical research.
My Latest Research
For my job market paper, I designed and conducted a survey experiment involving workers who had attended an unemployment agency, eliciting workers’ willingness-to-pay for remote work, (non-)surveillance by their employer, and worker voice: the influence that workers may exercise in their firm’s decision-making.
Personal Details
My hobbies include hiking and guitar, both classical and flamenco (the guitar that is; I hike in various genres).