16.1 Prediction

• Definition: Prediction, denoted as \(\hat{y}\), is about creating an algorithm for predicting the outcome variable \(y\) from predictors \(x\).

• Goal: The primary goal is loss minimization, aiming for model accuracy on unseen data:

  \[ \hat{f} \approx \min E_{(y,x)} L(f(x), y) \]

• Applications in Economics:

  • Measure variables.
  • Embed prediction tasks within parameter estimation or treatment effects.
  • Control for observed confounders.