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Introduction to Econometrics (Exercise) (Jonas Dix)

This course provides an overview of regression analysis. It centres around the question of how to identify causal effects from linear regression models that are estimated using the ordinary least squares (OLS) estimator. The main focus is to discuss the estimation of causal effects under mild identifying assumptions rather than the properties of the OLS estimator under ideal conditions that are of little practical relevance.

Contents:
1. About this course
2. The simple linear regression model
3. Inference in the simple linear regression model
4. The multiple linear regression model
5. Inference in the multiple linear regression model
6. Nonlinear regression functions
7. The validity of regression analyses

Students not only learn how to apply OLS regression appropriately, but also learn how to assess and scrutinise empirical analyses that use it and about its strengths and weaknesses. Moreover, students acquire the relevant skills to use OLS regression in own empirical analyses, e.g. in later empirical research projects or in their bachelor thesis.

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