Elena Manresa

Elena is an econometrician at the NYU department of Economics. Her research interests are in microeconometrics of panel data and applied microeconomics. She also has an interest in financial econometrics. The overarching theme of my research as an econometrician is the dealings of heterogeneity, both observed and unobserved, with machine learning and artificial intelligence tools. In spite of the focus of my work being on the methodological developments, I always display the usefulness of my methods through well-developed real world applications. Some examples of applications include the study of the origins of wage inequality using administrative data, quantifying R&D spillovers among firms, or rationalizing the wealth distribution among the eldest in the U.S.