Applied economists have long struggled with the question of how to accommodate binary endogenous regressors in models with binary and nonnegative outcomes. I argue here that much of the difficulty ...

The simplest form of regression in Python is, well, simple linear regression. With simple linear regression, you're trying to ...

Making individual predictions If we know the value of several explanatory variables for an individual, but do not know the value of that individual’s dependent variable, we can use the prediction ...

In recent columns we showed how linear regression can be used to predict a continuous dependent variable given other independent variables 1,2. When the dependent variable is categorical, a common ...

Methods to determine the validity of regression models include comparison of model predictions and coefficients with theory, collection of new data to check model predictions, comparison of results ...

The empirical model may also be used to construct a way to forecast the dependent variable, potentially helping policymakers make decisions about changes in monetary and/or fiscal policy to keep the ...

Multiple regression is where some independent variables are used (rather than just one, as in the example above), to predict one dependent variable. With Google Ads, I’ve found that there is ...

A lack of homoskedasticity may suggest that the regression model may need to include additional predictor variables to explain the performance of the dependent variable.