Simple linear regression model: Y = α+βX+ε, which is used to analyze the influence of independent variable X on dependent variable Y.
Multiple linear regression model: y = α+β1x1+β 2x2+…+β kxk+ε, which is used to analyze the influence of multiple independent variables on the dependent variable.
Discrete choice model: Y = 1 (choose one option) or Y = 0 (choose other options), which is used to analyze the decision-making behavior of individuals when facing different choices.
Time series model: yt = α+β1yt-1+β 2yt-2+…+β pyt-p+ε, which is used to analyze the relationship between time series data.
Panel data model: YIT = α+β1xit/+β 2xi2+…+β kxitk+UIT+ε it is used to analyze the relationship between panel data (i.e. cross-sectional data and time series data).
Difference estimation model: yt–yt-1= α+β1(XT–XT-1)+ε t, which is used to analyze the differences and changes between variables.