Fundamentals of Python for Financial Econometrics

Chapter 27: Potential Outcomes and Randomized Experiments

What does a causal effect mean for one unit, and why can we never observe both potential outcomes?

Loading notebook...potential outcomesindividual and average treatment effectsfundamental problem of causal inferencerandom assignment

Notebook lab guide

Related dataset

Ceteris Lab teaching sample

Estimated time

35 to 55 min

Packages

pandas, numpy

Expected output

Printed Python results that can be compared with the lesson explanation.

Learning goals

Load and inspect Ceteris Lab teaching sample.
Run the Python cells connected to Potential Outcomes and Randomized Experiments.
Interpret the output using potential outcomes and individual and average treatment effects.

Common errors

File not found: check that wage_sample.csv is installed or use the course data folder.
Package import error: use the browser notebook first, then download for local Jupyter if your local packages differ.
Column name error: compare your variable names with the dataset variables listed for this notebook.

Dataset path helper

import pandas as pd

df = pd.read_csv("/data/wage_sample.csv")
df.head()

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