Econometrics provides the methods that empirical economists use to learn from data. It is the bridge between data and economic theory, providing methods for both testing and refining theories and for using those theories to make quantitative predictions. It is also an interdisciplinary field, using tools from mathematics, statistics, computer science, and machine learning.
Recent econometrics research has studied how to analyze new kinds of data--like big datasets with many observations, many variables, or both, and high frequency datasets which record many observations in a short period of time. It has also provided new methods for analyzing traditional data sources, including methods for measuring sampling uncertainty and methods for understanding causality.
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Tim Bollerslev, Juanita and Clifton Kreps Distinguished Professor of Economics, in Trinity College of Arts and Sciences Professor Bollerslev conducts research in the areas of time-series econometrics, financial econometrics, and empirical asset pricing finance.
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Anna Bykhovskaya, Assistant Professor of Economics
Professor Bykhovskaya's research interests lie time series econometrics, with an emphasis on nonstationarity such as unit roots and cointegration. |
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Matt Masten, Associate Professor of Economics Professor Masten is an econometrician working on identification and causal inference. His current focus is on robustness and sensitivity analysis.
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Andrew Patton, Zelter Family Distinguished Professor Professor Patton’s research interests lie in financial econometrics, with an emphasis on forecasting volatility and dependence, forecast evaluation methods, and the analysis of hedge funds and mutual funds |
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Michael Pollmann, Assistant Professor of Economics Professor Pollmann’s research in econometrics focuses on causal inference and high-dimensional methods. |
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Adam Rosen, Professor of Economics
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