Es ist eine neuere Version 2023W dieser LV im Curriculum Master's programme Economic and Business Analytics 2024W vorhanden.
Workload
Education level
Study areas
Responsible person
Hours per week
Coordinating university
3 ECTS
M1 - Master's programme 1. year
Economics
Gerald Pruckner
2 hpw
Johannes Kepler University Linz
Detailed information
Original study plan
Master's programme Economic and Business Analytics 2022W
Objectives
Students master the fundamentals of econometrics.
They are familiar with the most important concepts of mathematical statistics such as estimation and testing.
They know the differences between different types of data and have experience in data collection and preparation.
They understand empirical economic papers and can also evaluate their quality.
They know the strengths and limitations of multiple regression analyses and can interpret estimation coefficients depending on different functional forms.
They are able to independently conduct simple empirical analyses using business and economic data and to interpret the results.
The students know the difference between descriptive and causal analysis.
They have an overview of the possibilities of causal identification.
Subject
Basic statistical concepts (samples, probability distributions and their moments, ...)
Estimation and testing
Cross sectional data, time series, and panel data
Descriptive analysis and graphical representations
The linear regression model
The multivariate regression model -- model specification
Introduction to causal identification
Criteria for evaluation
Written exam
Methods
Lecture
Study material
to be announced in lecture
Changing subject?
No
Earlier variants
They also cover the requirements of the curriculum (from - to) 977PADTEMEK21: KS Empirical Economics (2021W-2022S)
