A new method has been developed to figure out all the different effects of a variable in a regression model using just one binary instrument. By looking at differences in the first stage of the model, researchers can identify these effects without needing to worry about hidden factors. This method can also be applied to Regression Discontinuity Design, where adding more information can help with identification. Different types of estimators have been created based on this method, and they work well even with smaller sample sizes. This approach was used to study how air quality affects house prices, building on previous research.