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Empirical Economics

Latest News on April 11, 4:00 pm

  • The first lecture will take place on April 13

Basic Information


Course Description

The Module Empirical Economics will give the students an in-depth introduction into econometrics. We will have two lectures (L) and one class (C) per week for a total of 6 hours. The module is primarily aimed at bachelor 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 only assume a basic understanding of statistics and mathematics. Understanding of simple economic theory is, of course, an advantage.The module will be held during the summer semester and all parts should be simultaneously attended. (It is possible to exclusively attend the lectures, 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 statistics and linear algebra. We will then move onto the introduction to basic econometric tools. Although the use of mathematics and the formal derivation of the main results is inevitable for a method course, we will very much 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.

Instructor

Prof. Dr. Tomaso Duso

Office Hours

After the Lecture, or by appointment (E-mail: duso@dice.uni-duesseldorf.de, Tel: ??) Room ??

Registration

Do we have an automatic registration system? If not: Students will have to register providing their email address during the first lecture.

Course Plan


Copyright disclaimer: Part of the material reported in these slides is taken and adapted form the work of Matthew Leingang and Martin Halla, who I thank very much. My work is licensed under a Creative Commons Attribution-NonCommercial 3.0 Unported License.


 Room  Date  Topic  Material
L  G2  13.04.2011 Introduction Slides
L  G2  13.04.2011

C  G2  19.04.2011

L  G2  20.04.2011 Statistical refresher: estimation and testing I
Slides
L  G2  20.04.2011 Statistical refresher: estimation and testing II
 
C
 PC  26.04.2011 Stata: an introduction I
Do-Files I,
L
   27.04.2011 Statistical refresher: descriptive analysis I
Slides
L    27.04.2011 Statistical refresher: descriptive analysis I
C    03.05.2011 Stata: an introduction II
Do-Files II
L
   04.05.2011 Matrix algebra: vectors and matrices
Slides
L
   04.05.2011 Matrix Algebra: properties Slides
C    10.05.2011 Homework I

L
   11.05.2011 The linear regression model - I
Slides
L
   11.05.2011 The linear regression model - II
C
   17.05.2011 Homework II (Ch. 2)
L
   18.05.2011 Multiple Regression Analysis: Estimation (Ch. 3 ) I Slides
L
   18.05.2011 Multiple Regression Analysis: Estimation (Ch. 3 ) II

C
   31.05.2011 Homework III (Ch. 3-4)

L
   01.06.2011 Multiple Regression Analysis: Inference (Ch. 4 ) Slides
L
   01.06.2011 Multiple Regression Analysis: OLS Asymptotics (Ch. 5) Slides
C
   07.06.2011 Homework III (Ch. 5-6)
L
   08.06.2011 Multiple Regression Analysis: Further Issues (Ch. 6)
Slides
L
   08.06.2011 Multiple Regression Analysis: Binary Variables (Ch. 7) - I Slides
C
   14.06.2011 Homework (Ch 7-8)
 
L
   15.06.2011 Heteroskedasticity (Ch.More 8)  
L
   15.06.2011 More on Specification and Data Issues (Ch. 9)
 
C
   21.06.2011 Homework (Ch 8-9)
 
L
   22.06.2011 Basic Regression Analysis with Time Series Data (Ch. 10) - I
 
L    22.06.2011 Basic Regression Analysis with Time Series Data (Ch. 10) - II
 
C
   28.06.2011 Homework (Ch 10)
 
L    29.06.2011 Further Issues in Using OLS with Time Series Data (Ch. 11)
 
L
   29.06.2011 Serial Correlation and Heteroskedasticity (Ch. 12)
 
C
   05.07.2011 Homework (Ch 11-12)  
L
   26.07.2011 Pooling Cross Sections across Time: Simple Panel Data Methods - I
 
L
   26.07.2011 Pooling Cross Sections across Time: Simple Panel Data Methods - II
 
C
   05.07.2011 Homework (Ch 13)
 
L
   06.07.2011 Revision  
L
   06.07.2011 Revision  
C
   12.07.2011 Revision
 
L
   13.07.2011 Final Exam
 
L
   13.07.2011 Final Exam
 

Creative Commons License

Data used in the course


Books


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 all the assignments (20% of the final grade). They will be also asked to present one homework in front of the class (20% of the final grade).

Interesting links


Everything about econometrics
Something to read

Stata:

Data:

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  1115k v. 1 Apr 11, 2011, 8:37 AM Tomaso Duso
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