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Allgemeine Lehrveranstaltungsinformation

Lehrveranstaltungsziele

The students gain knowledge in the field of Ökometrie by empirical examples on the computer. 

Zielgruppe

Lehrveranstaltungsinhalte

• Multiple Regression Analysis
• Econometric Specification
• Data Issues
• Binary Variables
• Heteroskedasticity
• Basic Regression Analysis with Time Series Data

The Econometrics I IK is intended to be a complementary course to Econometrics I KS. While the KS's focus lies on econometric theory, the IK's emphasis is to provide a deeper understanding of the concepts covered in the KS and to apply econometric methods and tests to real data. The course aims particularly at developing practical skills which are necessary to perform independent empirical research. Students planning to attend this course should be familiar with the software pack STATA. The prerequisite course Empirische Wirtschaftsforschung IK - which provides a comprehensive introduction to STATA - is offered every winter term.

IMPORTANT:  You may find these STATA cheatsheets useful: click me

Lehrveranstaltungsvorraussetzungen

Einführung in die Betriebswirtschaftslehre, Einführung in die VolkswirtschaftslehreKernkompetenzen I aus Volkswirtschaftslehre
 

In order to successfully participate in this intensifiying course, students need also to enroll in the course "Econometrics I". Please, see the respective prerequisites there. Further information, in particular, the overall schedule of the econometrics classes, are available at http://www.econ.jku.at/1408/ . Please note that not all econometrics classes are offered every semester.

Prüfungskommission

Im Falle von kommissionellen Prüfungsantritten setzt sich die Prüfungskommission wie folgt zusammen:

  • Vorsitzender: Dr. Rudolf Winter-Ebmer
  • 1. Prüfer: Mag. Alexander Ahammer
  • 2. Prüfer: Dr. Franz Hackl

Literatur

  • Wooldridge, J. M. (2015) 'Introductory Econometrics: A Modern Approach,' 5th ed., South Western College Publishing.
  • Angrist, J. D. & Pischke, J. S. (2009, HME) 'Mostly Harmless Econometrics,' Princeton University Press.
  • Angrist, J. D. & Pischke, J. S. (2015, 'MM) 'Mastering Metrics,' Princeton University Press.
  • Greene, W. H. (2012) 'Econometric Analysis,' 7th edition, Pearson.
  • Searle, S. R. (1982) 'Matrix Algebra Useful for Statistics,' Wiley Series in Probability and Mathematical Statistics. 

Detaillierte Unterlagen (Passwort erforderlich)

Grading

Grading is based on three problem sets (10 points each, in total 30 points) and a presentation (30 points). 

Problem Sets: The problem sets will be made available here (soon). I advise you to solve them already during the semester whenever the corresponding topics come up in the KS. In May, we have three meetings (7th, 14th, and 28th) where some of you will be picked to present their solutions in class. Please read the instructions below carefully, and don't forget to turn in your do-file before class. In case you get picked to present, you are free to use your own laptop.

Presentation: At the end of the semester, students present an empirical paper which may include a small replication exercise as well (see information below). The grading scale follows the Austrian scholastic system and ranges from 5 ("Nicht genügend") to 1 ("Sehr gut").

More information can be found on the introductory slides, please read them carefully.

Meetings

Date Venue Topics Slides & Problem Sets
Mon, 05.03.2018, 13:45 - 15:15 K033C Introduction  Slides
Mon, 07.05.2018, 15:30 - 17:00 K033C Problem Set 1 Problem Set 1
Mon, 14.05.2018, 15:30 - 17:00 K033C Problem Set 2 Problem Set 2
Mon, 28.05.2018, 15:30 - 17:00 K033C Problem Set 3 Problem Set 3
Mon, 04.06.2018, 15:30 - 17:00 K033C Presentations I  
Mon, 11.06.2018, 15:30 - 17:00 K033C Presentations II  
Mon, 18.06.2018, 15:30 - 17:00 K033C Presentations III  

Problem Sets

Problem sets consist mainly of computer exercises which ought to be solved using statistical software (in class, we use STATA). Try to solve every exercise. However, if you get stuck or you don't know how to solve an exercise at all, explain why you got stuck or what the problem was. IMPORTANT: Comment on your results, especially tests and regression outputs should be interpreted carefully. Just providing the necessary commands is not sufficient to get credit.

How to hand in your solution 

I urge you to use this template for your do-files: template.do

  • Specify your working directory
  • Fill in your name and matriculation number
  • Make sure your do-file is structured clearly
  • Document important steps in your code, interpret your results
  • Make sure your do-file is EXECUTABLE!
  • Send the do-file to me via e-mail before midnight sharp, the subject should be
    Econometrics 1 IK Problem Set [x] k[your matriculation number]

    For example, Econometrics 1 IK Problem Set 1 k1234567.

More information can be found on the introductory slides, please read them carefully.

Presentation

Part of the grading will be based on a presentation you hold at the end of the semester. Please read the instructions carefully:

Instruction from last semester (will be updated shortly)
Doodle poll 

Please see the following guide on how to make good graphs and tables compiled by Martin Hallaclick me

Before your presentation, I would highly recommend to read chapter 1 of Angrist & Pischke's 'Mostly Harmless Econometrics' (MHE, you can find it here) and make sure to address all four FAQ's proposed therein. MHE is a great reference for applied econometricians - if you want to become one, read it. It's easily understandable and very non-technical, but covers all basic state-of-the-art econometric methods.

Data

Student data: Questionnaire | student_data_ss18.xlsx | student_data_skz.csv | student_data_clean.dta

File Description Download
AFFAIRS description dta | raw (do)
air2 description dta | raw (do)
ATTEND description dta | raw (do)
FERTIL3 description dta | raw (do)
INFMRT description dta | raw (do)
JTRAIN2 description dta | raw (do)
JTRAIN3 description dta | raw (do)
MEAP00_01 description dta | raw (do)
mus03data description dta | raw (do)
mus08cigar description dta | raw (do)
nhanes99ndi_extr description dta | raw (do)
nys1987_extr codebook & description dta | raw (do)
oecd_yu description dta | raw (do)
SLEEP75 description dta | raw (do)
SMOKE description dta | raw (do)
TWOYEAR description dta | raw (do)
WAGE2 description dta | raw (do)

Note: You should now be able to open the STATA files (*.dta) with version 8 or above. If it doesn't work, insheet the raw files by typing

insheet using <insert_filename_here>.raw, clear

and get variable labels by calling the corresponding do-file, i.e.

do <insert_filename_here>.do

Useful Links