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.