zagoodman

2008_ESA_nutrition

Code for "The Role of Liquidity in Food Choice: Evidence from the Economic Stimulus Act of 2008" by Z. Goodman

applied_metrics

A PhD course in Applied Econometrics and Panel Data

EconML

ALICE (Automated Learning and Intelligence for Causation and Economics) is a Microsoft Research project aimed at applying Artificial Intelligence concepts to economic decision making. One of its goals is to build a toolkit that combines state-of-the-art machine learning techniques with econometrics in order to bring automation to complex causal inference problems. To date, the ALICE Python SDK (econml) implements orthogonal machine learning algorithms such as the double machine learning work of Chernozhukov et al. This toolkit is designed to measure the causal effect of some treatment variable(s) t on an outcome variable y, controlling for a set of features x.

ironman

Analysis of Ironman triathlon finisher data

mediumish-theme-jekyll

Jekyll Template - Mediumish

micro-metrics

This is a 2nd Year PhD Course In Micro-econometrics

microeconomics_videos

Analysis of the Microeconomics Video Handbook experiment by Famulari and Goodman

predictit

SMS notifications for new PredictIt markets

real_travel_cost

required_homework

Analysis of the Required Homework experiment by Antonovics, Famulari, and Goodman

zagoodman/ironman

Analysis of Ironman triathlon finisher data

zagoodman/2008_ESA_nutrition

Code for "The Role of Liquidity in Food Choice: Evidence from the Economic Stimulus Act of 2008" by Z. Goodman

zagoodman/applied_metrics

A PhD course in Applied Econometrics and Panel Data

zagoodman/EconML

ALICE (Automated Learning and Intelligence for Causation and Economics) is a Microsoft Research project aimed at applying Artificial Intelligence concepts to economic decision making. One of its goals is to build a toolkit that combines state-of-the-art machine learning techniques with econometrics in order to bring automation to complex causal inference problems. To date, the ALICE Python SDK (econml) implements orthogonal machine learning algorithms such as the double machine learning work of Chernozhukov et al. This toolkit is designed to measure the causal effect of some treatment variable(s) t on an outcome variable y, controlling for a set of features x.

zagoodman/mediumish-theme-jekyll

Jekyll Template - Mediumish

zagoodman/micro-metrics

This is a 2nd Year PhD Course In Micro-econometrics

zagoodman/microeconomics_videos

Analysis of the Microeconomics Video Handbook experiment by Famulari and Goodman

zagoodman/predictit

SMS notifications for new PredictIt markets

zagoodman/real_travel_cost

zagoodman/required_homework

Analysis of the Required Homework experiment by Antonovics, Famulari, and Goodman

zagoodman/ssb_taxes

Code for "The Effect of Sugar-Sweetened Beverage Taxes in the United States: Evidence from Scanner Data" by J. Orchard and Z. Goodman

zagoodman/swallow

Predict swallow volume using wearable sensor data

zagoodman/zagoodman.github.io

Personal website for Zack A. Goodman