The course contains:
• Stochastic limit theory
• Linear algebra
• Data generating processes
• The linear regression model
• The least square estimator
• Hypothesis tests and model selection
• Functional form and structural change
• Nonlinear and nonparametric regression models
• Endogeniety and Instrumental Variable estimation
• The generalized regression model
• Systems of equations
• Models for panel data
• Estimation methodology
• Truncation, censoring and sample selection
• Time series analysis

Course information

Number of credits

15 credits

Given by

School of Business and Economics

Open to

Each student should be accepted as a doctoral student in Business Administration/Economics/Statistics. 30 credits in statistics or econometrics is needed as a very minimum. Basic skills in matrix algebra is recommended

Teaching language




Next course occasion

Spring 2024

Study rate, or the equivalent

Full time studies