Empirical Methods

Oliver Kirchkamp, Thu. 12-14, KU Hörsaal, Bachstraße 18K , [Friedolin]
Dr. Olexandr Nikolaychuk, Fri., 10-12, Carl Zeiss Str. 3, HS 8.
Tue., 12-14, Carl Zeiss Str. 3, HS 4, [Friedolin].
Discussion board:
Please use the discussion board of this course to ask questions and discuss issues related to the lecture.
42Review of probability and statistics
43Dies academicus (no lecture, only exercise)
44Review of frequentist inference
45Review of linear Regression
46Review of models with multiple regressors
47Midterm exam (1/3) (no lecture or exercise in this week)
49Bayesian methods (Resit of Midterm)
50Bayes in practice
51Binary choice
2More on discrete choice
3Mixed effects models
4Instrumental variables
5Model comparison
6Summary, revision
To get a credit for the course students have to pass the midterm (1/3 of the total grade) and the final exam (2/3 of the total grade, please keep in mind that grades for the course must be rounded!).

You can take the final exam even if you have failed the midterm. You pass the course only once you have passed both parts. (E.g. you can pass the final in one year and the midterm in another year to get the credit.) You must be registered for the exam in Friedolin to get a credit for the course.

Midterm (1/3):
Thu., 22.11.2018, 18:00, Carl Zeiss Str. 3, HS 1[Friedolin]

  • To register for the midterm students register for the course at least 10 days before the midterm exam through Friedolin. Please register for the course and for the exam! (If it is for some reason impossible to register for the exam during the first weeks of the term you can still take the midterm if you only register for the course. However, to take the final exam you have to register in Friedolin for the exam!)
  • Exchange students who can not register for the course with Friedolin complete this form on their computer.
Candidates then get an e-mail (to their uni-jena address) with their assigned seat for the midterm.

Students will also receive the midterm results (and, in case they failed, their seat for the resit) at their uni-jena address. Students who send their public PGP key to oliver.kirchkamp@uni-jena.de before the midterm will receive their results encrypted to their key.

Candidates who have earlier passed either the midterm or the final but not both parts have two options for the exams they take this term:

  • They register for the exam, but show up only for the part they did not pass in the past. In this case I will credit the result of the previous attempt of the other part for this term.
  • They register for the exam, and show up for both parts, midterm and final. In this case the result of this term counts for the final result. (This holds even if this term's result is a fail!)
Students who do not register for the exam do not obtain any credits.
  • Instructions for the midterm.
  • Resit of the midterm: Thu., 6.12.2018, 18:00, Carl Zeiss Str. 3, HS 3. [Friedolin]
    • Students who took the midterm and who failed are automatically registered for the resit. No extra registration is needed in this case. (Please note that for the resit of the final exam you must register with the examination office.)
    • Students who missed the first take because they were ill and who present a certificate from their physician within three days after the missed exam will participate in the resit. These students complete this form on their computer.
    • Students who passed the first take can't take the resit.
    • Students who did not show up for the first take and who were not ill don't take the resit.
Final exam (2/3):
18.02.2019, 10-12, Carl Zeiss Str. 3, HS 1. You must register in Friedolin for the exam (not simply for the course), even if you have passed the midterm earlier.

Exchange students who can not register for the course with Friedolin complete this form on their computer.

Other material:
  • Handout (contains all the slides):
  • Previous exam questions
  • Requirements:
    Basic mathematical and statistical methods as, e.g., in BW24.1.
    To learn more, I recommend the following textbooks. You find further recommendations at the end of each chapter in the handout. (If you find not enough copies of the books you need in the library, please tell the librarians. If you do not tell them, nothing will change.)
    Examples from the lecture:
    In the lecture I will often use practical examples as illustrations. I recommend that you try these examples on your own. To do this, open R and type the following:
    from now on all commands refer to this dataset, e.g.: plot(str,testscr), or
    A brief documentation of the variables of this dataset can be obtained with help(Caschool)
    For our practical examples (during the entire course) we will use the software environment R. I think that it is helpful to coordinate on one environment and R has the advantage of being free and rather powerful.

    For the Bayesian parts we will use JAGS. It helps if you have installed R and JAGS on your computer when we start the course.

    For the Bayesian part we will use the library runjags and the software JAGS