Incorrectly labeling variables in models may lead to flawed economic predictions.
Estimators in economics need to have enough data on certain variables to work properly. This study looks at ways to figure out which variables are important and which aren't, and what happens if we get it wrong. They found that sometimes using the wrong variables can actually give better results than using the right ones. This means that we need to be careful when choosing which data to use when studying things like how education affects how much money people make.