Q1: Propensity score matching and endogenous switching regression are two different methods used in statistics and econometrics to address issues related to selection bias and endogeneity in observational data. Ex: Purpose:

• Propensity Score Matching, Endogenous Switching Regression

Nature of Approach:

• Propensity Score Matching, Endogenous Switching Regression

Handling Bias:

• Propensity Score Matching, Endogenous Switching Regression

Data Requirements:

• Propensity Score Matching,Endogenous Switching Regression

Q2: Both Propensity Score Matching (PSM) and Endogenous Switching Regression are used in impact analysis to address different issues related to observational data and treatment effects. They can be applied under specific conditions based on the nature of the data and the underlying assumptions.to determine which model to use:

• For Selection Bias Correction: If the main concern is correcting for selection bias based on observed characteristics, PSM is more appropriate.
• For Addressing Endogeneity: If the focus is on addressing endogeneity due to unobserved factors impacting both the selection process and the outcome, then endogenous switching regression is more suitable.