Hi😊 I am Jared Amani Greathouse. Currently, I am a public policy PHD candidate at Georgia State, where I am fortunate to be advised by Jason Coupet. Prior, I earned my Bachelors and Masters in political science from Georgia State University. I am the author of the mlsynth Python package, the largest open source synthetic control package in the world.

I am an econometrician specializing in causal inference, particularly with the synthetic control method. My current work focuses on high-dimensional data and machine learning methods for treatment effect estimation. If causal inference is your thing, check out the software I develop for Stata and Python. Check out my blog, “Policy Analysis, Data Science, and Causal Inference”. Here I discuss causal inference, econometrics, and other data science topics for policy analysts. I am also an active contributor to the Statalist forum. Here’s my vita.

If you’d like to talk with me about my work, my consulting services, or anything else that is of interest, you may always reach out to me!

• Email: jgreathouse3[at]student[dot]gsu[dot]edu

Here is a plot generated via GitHub Actions, a tool we may use to automate data collection/repetitive tasks:

• Here is a dashboard of scraped Spotify data I developed with Streamlit.

News

• Here are my slides (still being developed) that introduces the synthetic control method.

• As of August 29, 2025, the landing page for mlsynth is up.

• As of October 6th, 2024, my draft of an empirical replication is available, where I compare and contrast the findings of the Forward DID method versus the fsPDA, using the Chinese Anti-Corruption Campaign as an example. Here is the replication code.

• As of September 27th, my draft for the Forward DID method is avaliable. Here is the link to read it. Note that it is has not been submitted for review yet. Any comments or feedback would be appreciated.