Econometrics: A Causal Approach – January 2022

Event Phone: 1-610-715-0115

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In the unlikely event that Statistical Horizons LLC must cancel a seminar, we will do our best to inform you as soon as possible of the cancellation. You would then have the option of receiving a full refund of the seminar fee or a credit towards another seminar. In no event shall Statistical Horizons LLC be liable for any incidental or consequential damages that you may incur because of the cancellation.
A 3-Day Remote Seminar Taught by Nick Huntington-Klein, Ph.D.

This course offers a survey of econometrics. Econometrics is a broad category of data analysis that focuses on trying to use data to understand how the world works, even in cases where you can’t run an experiment. The seminar puts an emphasis on practical understanding and use of these concepts, as opposed to statistical proofs.

Over the course of three four-hour sessions, we will cover regression analysis, identification, and some common research designs.

Regression is the primary tool that econometricians use to evaluate data. We’ll be going over how regression is used in econometrics, including the many ways econometricians grapple with the parts of the world we don’t understand yet – error terms. Identification is how econometricians link theory (economic theory or otherwise) to data, and determine not just the difference between correlation and causation, but more broadly whether our analysis is actually answering the question we want it to. Identification is a broad idea, but there are a few standard research designs that can help us a lot, and we’ll be covering modern developments in fixed effects, difference-in-differences, regression discontinuity, and instrumental variables.

Specific topics covered will be linear regression, heteroskedasticity-, autocorrelation-, and cluster-robust standard errors, identification, omitted variable bias, directed acyclic graphs, fixed effects, difference-in-differences, regression discontinuity, and instrumental variables. There will also be a brief overlook on how machine learning is likely to change how econometrics is performed.

We will focusing on the R programming language in the lab portions of the class. However, all materials will also be made available in Stata and Python, and assistance will also be available in those languages.

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