The aim of Applied Statistics and Econometrics is to provide an introduction to the practice of econometrics. While both theoretical and practical aspects are covered, emphasis will be on intuitive understanding and concepts will be illustrated with real-world applications.

Throughout, we will focus on both understanding and doing. The understanding will come from lectures, class discussions, and problem solving. The doing will come from extensive statistical software use. This course requires a quarter-long commitment. Econometrics is best learned by doing, and I will require you to do a fair amount of hands-on work.

For further details about the structure of the course, please download the syllabus. The syllabus has information about this course. In particular, it has information on how, where and when to contact me and the teaching assistants; an outline of the course content, the schedule of exam dates; the grading policy, and other important organizational details of the course. You can find some of this information on this web page, but not all. So, please, refer to the syllabus for any questions you may have about the course.


Lecture content

n. date topic
01 M 13-02-2016 Introduction to econometrics
02 T 14-02-2016 Review of statistics
03 M 20-02-2016 Review of statistics I
04 T 21-02-2016 Review of statistics II
05 M 27-02-2016 Bivariate regression I
06 T 28-02-2016 Bivariate regression II
07 M 06-03-2016 Bivariate regression III
08 T 07-03-2016 Endogeneity and causality
09 M 13-03-2016 Multiple regression I
10 T 14-03-2016 Multiple regression II
11 M 20-03-2016 Nonlinear regression models I
12 T 21-03-2016 Nonlinear regression models II
13 M 27-03-2016 Assessing regression studies
14 T 28-03-2016 Midterm
15 M 03-04-2016 Binary dependent variable I
16 T 04-04-2016 Binary dependent variable II
17 M 10-04-2016 Panel Data I
18 T 11-04-2016 Panel Data II
19 T 24-04-2016 Instrumental variables regression I
20 M 02-05-2016 Instrumental variables regression II
21 T 03-05-2016 Instrumental variables regression III
22 M 08-05-2016 Program evaluation I
23 T 09-05-2016 Program evaluation II

There will be a weekly problem set. The assignments will involve both theoretical and empirical work. Group study and free discussion are encouraged. But you should submit your own answers. You will probably find the class very hard to follow if you fail to spend sufficient time on all of the problem sets. The problem sets are part of the final grade as explained in the next section below.

If you have any question on the problem sets, please ask me or TA’s during our office hours. Our office hours are for you. I prefer to talk to you in person. I feel that Email is not a very efficient way to ask econometric questions.

Problem set answers are to be turned in on time. You can hand in the homework AFTER the class. Please do not come and hand it in to me whilst I am lecturing. Do not email assignments. Late solution will not be accepted!

Problem sets

  • Problem Set 1

  • Problem Set 2 (Due Tuesday, March, 7 2017)

    Note: This problem set is multiple choice. You have to print the answer sheet, fill your id, and fill your answers based on the questions.

  • Problem Set 3 (Due Thursday, March 16 2017) This problem set is personalized. Each student must download her own version of the problem set. To download the problem set use the following URL: where xxxxxx is the LUISS ID of the student.

The TAs will lead a weekly practice session which will be held in the computer labs (301 and 306).

The TA sessions are an important part of the course and regular and attendance is strongly encouraged. During these sessions, the TA will review the concepts introduced in class and solve applied problems using R.

The sessions are also the right place to ask questions about the problem set of the week.

The following table gives the distribution of students across the two sessions:

TA Where Time Students
Siria Angino A301 W 14:00-15:30 G-Z
Giuseppe Brandi A306 W 18:30-20:00 A-F


The software used in this course is R. No prior knowledge of this software package is assumed. This package will be introduced in the TA Sessions.

R is installed on all computers in the computer lab. Since R is open source you can freely install it on your laptop or desktop. R is available for all major computing platforms: Windows, Mac OSX, and Linux. Platform specific installation help can be found at here.

I recommend using R through Rstudio, a free and open source integrated development environment (IDE) for R. Rstudio is installed on most computers in the computer labs where TA sessions are held. You can easily install Rstudio on your machine by following the instruction here.

ASE 2016-2017

Instructor: Giuseppe Ragusa

Teaching assistants:

  1. Siria Angino
  2. Giuseppe Brandi

Office hours

  • Angino: W, 16:00-17:00

  • Brandi: W, 9:30-11:00

  • Ragusa: T, 11:30-13:00


  • Problem set 3 posted
  • Problem set 2 posted
  • Problem set 1 posted


Giuseppe Ragusa teaches in the Department of Economics and Business and in the Business School at Luiss University. His research is mostly about econometrics.



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