Econometrics

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Basic Information

Course Description

This course will give the students an in-depth introduction into econometrics tools. We will have one lecture (L) and one class (C) per week for a total of 6 hours. The course is primarily aimed at master students whose main focus is economics (VWL), but it is also open to students whose main focus is business administration (BWL), or students of other disciplines in social and economic sciences who are interested in empirical questions and methods. We will assume a basic understanding of statistics and mathematics. Preliminary econometrics knowledge (see my bachelor course Empirical Economics) is very useful. Understanding of simple economic theory is, of course, an advantage.The course will be held during the winter semester and all parts should be simultaneously attended. (It is possible to exclusively attend the lecture, but it is absolutely NOT recommended... in particular, because the class will be the fun part!)

We will start with a refresher of basic concepts in linear algebra. We will then move onto the introduction to basic econometric tools. After introducing the basic concepts from asymptotic theory, we will move to the analysis single-equation linear model. We will discuss Ordinary Least Squares (OLS) estimation and Instrumental Variable (IV) estimation. We will then move to multiple-equations models. We will finish with an introduction to basic unobserved effects panel data models. Although the use of mathematics and the formal derivation of the main results is inevitable for a method course, we will still have a particular focus on relevant (economic) applications and the use of data to enhance the students' understanding of the usefulness of the material learned. The lectures are especially aimed at developing the ability to understand empirical tools and will be, therefore, more formal.The focus is mainly on the derivation of different empirical approaches, the intuition behind them, but also the identification of the limits of these methods. In the class, we will apply these methods to real data. Therefore, we will also introduce the students to the econometric software package Stata. Hence, during the course, students will learn to formulate simple empirical questions, collect relevant data, select appropriate empirical methods to be applied to the data, and formulate a meaningful interpretation of the empirical results of their analysis.

By the end of the module students will have acquired the necessary skills and knowledge to be able to critically appraise work in the area of applied economics. They will have a good intuitive and theoretical grasp of the uses, pitfalls and problems encountered when doing applied modeling. The module will also equip students with the necessary background material to be able to go on to study more advanced and technical material in the area of econometrics. The skills developed in this module are not only necessary in the context of economic analysis, but also very valuable in practice for the assessment of any policy discussions.

Instructors

Prof. Dr. Tomaso Duso,

Dipl. Vw., Dipl Kfm. Joahnnes Muck

Office Hours

After the Lecture, or by appointment (E-mail: duso@dice.hhu.de, Tel: 10235) Room 24.31.01.17

Registration

You have to register for this class. Moreover, we will collect students' email address during the first lecture so that we can update you about the weekly news.

Data used in the course

• Used during the Lecture:
• Life expectancy, 2002
• CPS September, 2006 - description (short version, full version)
• Used during the Class:
  • BWGHT.dta
  • CEOSAL2.dta
  • WAGE.dta
  • BWGHT2.dta
  • MORTGAGE.dta
  • HOME.dta
  • SCHOOLING.dta

Books

• Wooldridge, Jeffrey M. (2009), Introductory Econometrics: A Modern Approach, 4th Edition, South Western College Publishing, Mason (Ohio).
• Wooldridge, Jeffrey M. (2010), Econometric Analysis of Cross Section and Panel Data, 2nd Edition, The MIT Press, Cambridge (MA).
• Greene, William H. (2007), Econometric Analysis, 6th Edition, Prentice Hall.
• Davidson, Russell and James G. MAcKinnon (2004), Econometric Theory and Methods, Oxford University Press(New York).

Preparation

• Lecture: Please read and think through each chapter from the textbook before the course and note unclear issues and questions that we will answer during the lecture when we present/discuss the chapter.
• Class: During the first weeks you will get an introduction in Stata. In the following weeks groups of students will present their solution to the assignments. After their presentation we will have a common discussion of the results and solution.

Evaluation

• Final Exam: oral examination or written exam (90 minutes) depending on the number of students (60% of the final grade)
• Homework assignments: In the tutorials students will be asked to solve four assignments (40% of the final grade).

Interesting links

Everything about econometrics

• Econometric Textbooks links by Econometrics Journal
• (US-focused) Econometric Resources by John Kane

Something to read

• Vox: The economists' voice
• Research-based policy analysis and commentary from leading economists
• Ökonomenstimme
• Die Internetplattform für Ökonomen im deutschsprachigen Raum
• The economics of beauty
• 'Beauty and the labour market', Interview with Daniel S. Hamermesh (University of Texas, Austin)
• 'The Economics of Teeth, and Other Beauty Premiums', Freakonomics Blog - NYTimes.com
• The economics of obesity:
• Trends in den USA, 1985-2008, (Center for Disease Control and Prevention)
• 'Health Reform and Obesity', by Richard A. Posner (02.08.2009)
• Wieso ist es gut Statistik zu kennen
• Statistik zwischen Klamauk und Analphabetismus von Hans Wolfgang Brachinger

Stata:

• 'Stata Tutorial' des Carolina Population Centers
• 'Rudiments of Stata' von Jeffrey M. Wooldridge
• 'Introduction to Stata' von Christopher F. Baum
• 'Stata Tutorial' - Princeton University
• 'Stata for Researchers: Introduction' - Social Science Computing Cooperative
• 'Stata Learning Modules' - UCLA
• 'Stata Graph Examples' - UCLA

Data:

• Databases
  • Portal Statistik (Datensätze bei Wikipedia)
  • National Bureau of Economic Research (NBER), Data Library
  • OECD Statistics Portal
  • World Bank Data
  • World Facts Book (CIA)
  • Statistische Bundesamt
• International Organizations
  • European Union (Eurostat, European Central Bank)
  • Organisation for Economic Co-operation and Development (OECD)
  • United Nations (WHO, World Bank)
  • World Trade Organization