363-0570-00L Principles of Econometrics
|Semester||Spring Semester 2020|
|Lecturers||J.‑E. Sturm, A. Beerli|
|Periodicity||yearly recurring course|
|Language of instruction||English|
|Comment||Prerequisites: previous knowledge in economics.|
|Abstract||This course introduces the fundamentals of econometrics. We cover simple and multiple regression analysis using different data formats. An emphasis is on hypothesis testing, interpretation of regression results, and understanding threats to the causal interpretation of relationships in the data.|
|Objective||The course targets both the theoretical understanding as well as the application of basic econometric methods to real world problems. |
The educational objective of this course is that, after completion, students should be able to:
1. understand different forms of data (cross-sectional, panel, time-series) and their strengths and weaknesses for answering different research questions.
2. understand how to translate questions about economic policy issues and human behaviour into research hypotheses that can be tested with data.
3. apply their theoretical knowledge about econometrics to concrete examples based on the knowledge they acquired in tutorial sessions using the statistical software package STATA and interpret estimation results.
4. name and identify potential threats for causal interpretations of relationships in the data and explain whether (and how) they can be addressed.
|Content||The term “econometrics” stands for the application of specific statistical methods to the field of economics. Econometrics aims at providing empirical evidence using observational data that can be used to learn about the real-world existence of specific relationships postulated in economic theories. Typical research questions that economists analyse by using econometric methods include for instance: Do minimum wages reduce employment? Does a gender wage gap exist and how large is it? Does foreign aid affect economic growth? How do interest rate changes influence exports? Is there an effect of economic outcomes on politicians’ chances to get re-elected? |
Starting from simple regression analysis, the course introduces the statistical framework that is used in econometrics to answer such empirical research questions. A major focus is on understanding and mastering methods of hypothesis testing using multiple regressions.
The lecture discusses different issues regarding assumptions, interpretation, and inference in multiple linear regression models. Among others, the course addresses the following questions: How well or badly does the applied model fit the observed facts? How large is the estimate of the effects of one variable on another and how reliable is the estimate? Can the model be used to predict the specific variable of interest and how precise is that prediction? What are the crucial assumptions of the estimation strategy used, (how) can they be tested, and does the estimated relationship represent a causal effect?
The course lectures introduce the methods and computer tutorials give the students the opportunity to apply and deepen their knowledge using the software package STATA.
|Literature||Wooldridge, Jeffrey M. (2018) Introductory Econometrics : A Modern Approach. Seventh ed. ISBN: 978-1-337-55886-0 [access to relevant chapters will be provided]|
|Prerequisites / Notice||This course is intended for students interested in econometrics who have already taken an introductory course in economics (e.g., the course "Principles of Macroeconomics"). Knowledge of the statistical software STATA is no prerequisite and will be acquired during the course.|