Guiding Research at the Intersection of Econometrics and Machine Learning

The Economic Machine Learning Lab is led by two faculty directors whose complementary expertise shapes the lab's research agenda, collaborations, and student development. Together, they support projects that connect econometric theory, machine learning methods, and applied economic questions.

Executive Director

Provides strategic leadership for the lab, including institutional direction, external partnerships, student development, and the broader integration of EML research with the lab's mission.

Research Director

Guides the lab's research agenda, with emphasis on methodological development, research standards, collaborative projects, and the scientific direction of EML work.

Yoosoon Chang

Yoosoon Chang

Professor of Economics
Executive Director, Economic Machine Learning Lab

Executive DirectorEconometricsMachine Learning

Background & Research Agenda

Yoosoon Chang is Professor of Economics at Indiana University and Executive Director of the Economic Machine Learning Lab. Her work connects econometric theory with inference for macroeconomic, financial, environmental, and distributional questions.

Her recent research focuses on functional time series, endogenous regime-switching models, high-frequency factor models, and applications involving intergenerational mobility, climate change, income distributions, inflation forecasting, yield curves, labor force participation, energy demand, and empirical asset pricing.

Research Interests

EconometricsMachine LearningEmpirical MacroeconomicsEmpirical FinanceEnergy EconomicsClimate ChangeInequalityIntergenerational Mobility

Email: yoosoon@indiana.edu

Office: Wylie Hall, Room 354

Education: Ph.D., Yale University

Joon Y. Park

Joon Y. Park

Professor of Economics
Wisnewsky Professor, Human Studies
Research Director, Economic Machine Learning Lab

Research DirectorEconometric TheoryTime Series

Background & Research Agenda

Joon Y. Park is Professor of Economics, Wisnewsky Professor in Human Studies, and Research Director of the Economic Machine Learning Lab. His research and teaching interests include econometric theory, time series, and financial econometrics.

His recent research focuses on inference for continuous-time models and the estimation and testing of asset pricing models using discrete-time, high-frequency economic and financial data. His foundational work on nonstationary time series has contributed to the understanding of economic models with nonstationarity in mean or volatility.

Research Interests

Econometric TheoryMachine LearningFunctional Data AnalysisTime SeriesFinancial EconometricsNonstationary Time SeriesContinuous-Time ModelsHigh-Frequency Data

Email: jpark@indiana.edu

Office: Wylie Hall, Room 215

Education: Ph.D., Yale University