Cristobal Young

Cristobal Young serves as an Associate Professor in the Department of Sociology within Cornell University's College of Arts and Sciences. His academic work bridges economic sociology, social stratification, and advanced quantitative methodology, with a particular focus on policies affecting income inequality.

Young's primary research interests center on the social consequences of economic policies, particularly examining how taxation of high-income earners affects mobility patterns, the wellbeing impacts of unemployment, and the extension of consumerist logics into domains like healthcare and education. His methodological expertise focuses on big administrative data, model uncertainty, and techniques for producing robust research results through multiverse analysis approaches.

His publication portfolio reveals consistent engagement with policy-relevant sociological questions, particularly in economic sociology and stratification research. Young frequently employs sophisticated quantitative methods to address questions about tax policy effects, unemployment consequences, and methodological challenges in social research. His work often generates significant public discourse, as evidenced by coverage in major media outlets including the New York Times, Wall Street Journal, and The Guardian.

Notable recognition includes:

• Granovetter Prize for best article in economic sociology

Young actively contributes to academic discourse through publications in top sociology journals and books that address methodological challenges in social science research. His teaching includes courses on inequality and big data analysis, reflecting his research expertise. While specific grant information isn't detailed in the available materials, his research on tax policy and unemployment suggests engagement with significant social policy questions that often attract research funding.

His work on multiverse analysis represents a significant methodological contribution to addressing the replication crisis in social science, offering systematic approaches to exploring how analytical choices affect research findings.