Econometrics II
Code: 102307Credits: 6
| Degree programme | Type | Course |
|---|---|---|
| Business Administration and Management | OP | 4 |
| Economics | OB | 3 |
Contact lecturer
- Name :
- Luca Gambetti
- Email :
- luca.gambetti@uab.cat
Teaching staff
- Pierre Magontier
Group languages
You can consult this information at the end of the document.
Prerequisites
It is highly recommended that the student has successfully completed Mathematics I, II, Statistics I, II and Econometrics I. Having full command of the materials presented in these courses is essential to succeed in Econometrics II.
Objectives
Econometrics II progress in the study and application of the linear regression model introduced in Econometrics I. After a brief review, the course introduces three deviations from the standard assumptions of the lineal model: heteroskedasticity , autocorrelation of the error terms and endogeneity of the explanatory variables. The students should learn the limitations of the classical model and how adapt this model and these methods for processing data associated with more general characteristics. For the same purpose it is introduced the maximum likelihood estimation method to allow the study of non-linear models, such that Logit and Probit Models. Throughout the course numerous examples using real data will be presented to help students to apply the introduced tools. We will put special emphasis to present the theoretical aspects in the most intuitive way. The main goal of this course is to provide students a deeper knowledge of the main econometric methods.
Learning outcomes
- Select and generate the information needed for each problem, analyse it and make decisions based on this information.
- Make decisions in situations of uncertainty and show an enterprising and innovative spirit.
- A capacity of oral and written communication in Catalan, Spanish and English, which allows them to summarise and present the work conducted both orally and in writing.
- Demonstrate initiative and work independently when required.
- Work as part of a team and be able to argue own proposals and validate or refuse the arguments of others in a reasonable manner.
- Use available information technology and be able to adapt to new technological settings.
- Use information technology programmes to perform a quantitative analysis of the data.
- Specify models, estimation methods and inference.
- Identify and apply the appropriate econometric methodology to respond to the problems appearing in the empirical study of some economic data.
- Analyse the performance of economic time series and make forecasts.
- Demonstrate initiative and work independently when required.
- Assess ethical commitment in professional activity.
- Students must have and understand knowledge of an area of study built on the basis of general secondary education, and while it relies on some advanced textbooks it also includes some aspects coming from the forefront of its field of study.
- Students must be capable of applying their knowledge to their work or vocation in a professional way and they should have building arguments and problem resolution skills within their area of study.
- Students must be capable of collecting and interpreting relevant data (usually within their area of study) in order to make statements that reflect social, scientific or ethical relevant issues.
- Students must be capable of communicating information, ideas, problems and solutions to both specialised and non-specialised audiences.
- Students must develop the necessary learning skills in order to undertake further training with a high degree of autonomy.
Contents
Unit 1: Review of the linear regression model
Unit 2: Heteroskedasticity
Unit 3: Endogeneity and the Instrumental Variables Estimator
- Models with Endogenous Explanatory Variables
- The Instrumental variable Estimator
- Case Studies: experiments and quasi-experiments
Unit 4: Regression analysis with Panel Data
- Panel Data with two time periods
- The fixed effects model
- Case Studies
Unit 5: Time Series Models
- Characteristics of Time Series
- ARMA models
- Forecasting
- VARMA models
Learning activities and methodology
| Title | Hours | ECTS | Learning outcomes |
|---|---|---|---|
| Laboratory Sessions | 17 | 0.68 | 1, 2, 5, 6, 7, 8, 9, 10 |
| Lectures | 32.5 | 1.3 | 1, 9, 10 |
| Studying and problem solving | 93 | 3.72 | 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12 |
The course activities will be structured as follows:
1. Lectures
In the lectures, the key concepts and methods will be presented by professor, using examples to facilitate a clear understanding of the materials presented.
2. Computer room activities
In order to better grasp the different econometric concepts and methods some lectures will take place in the computer room. The econometric package Gretl, an open source software program already used in Econometrics I, will be used extensively. Students will learn additional advanced menu options and estimation methods..
3. In class problem solving
There will be problems set for each unit and it is expected that students will work on them in groups or on their own. This activity is crucial to assimilate the theoretical aspects and the applications of the tools presented. The instructor will select some exercises from the problems set list to be discussed in class, although students are expected to complete the entire problems set in their own time.
4. Office hours
Students can use instructor's office hours to solve specific questions. Office hours will be announced in either the intranet (Campus Virtual) or in the instructor's webpage.
5. Studying
It is expected that activities 1 to 4, described above, take about one third of the time that the student is supposed to dedicate to Econometrics II. In order to succeed in this course, students should anticipate spending additional hours of The proposed teaching methodology may undergo some modifications according to the restrictions imposed by the health authorities on on-campus courses.independent work in problem solving and studying.
The proposed teaching methodology may undergo some modifications according to the restrictions imposed by the health authorities on on-campus courses.
Important:
-To successfully pass this course, class attendance is critical.
-For a good class environment: Everybody should arrive on time and plan on staying for the entire class.
Assessment
Continuous assessment activities
| Title | Weight | Hours | ECTS | Learning outcomes |
|---|---|---|---|---|
| Final Exam | 50% | 2 | 0.08 | 1, 2, 3, 4, 8, 9, 10, 13, 14, 15, 16, 17 |
| Submission of exercises | 20% | 4 | 0.16 | 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12 |
| Midterm exam | 30% | 1.5 | 0.06 | 1, 2, 3, 4, 8, 9, 10, 11, 12 |
1. Midterm exam
There will be a midterm covering the contents of Unit 1, 2 and 3. It will be a closed book exam. Grades will be given on a scale of 0 to 10. This exam will represent 30% of the overall course grade.
2. Final exam
There will be a final exam covering the contents of Unit 1, 2, 3, 4 and 5. It will be a closed book exam. Grade will be given on a scale of 0 to 10. This exam will represent 50% of the overall course grade.
3. Submission of exercises
Occasionally, each student will be asked to submit some exercises. The instructor might ask students to solve these exercises during class, during an evaluation session or in the way he sees fit. Grades will be given on a scale of 0 to 10. Exercise solving will represent 20% of the overall course grade.
Grading Policy
a. After the final exam grade is available, a course grade will be given to assigned to each student. As explained, the course grade is calculated according to the following expression:
COURSE GRADE=0.2*EXERCISES + 0.3* MIDTERM + 0.5*FINAL
b. To pass the course the course grade should be at least 5.
c. All students must take exams and turn in assignments on their specified dates. No exceptions possible.
d. If a student has not participated in any of the evaluations activities(midterm exam, final exam, submission exercises) recive a grade of ”No avaluable\"
Calendar of evaluation activities
The dates of the evaluation activities (midterm exams, exercises in the classroom, assignments, ...) will be announced well in advance during the semester.
The date of the final exam is scheduled in the assessment calendar of the Faculty.
\"The dates of evaluation activities cannot be modified, unless there is an exceptional and duly justified reason why an evaluation activity cannot be carried out. In this case, the degree coordinator will contact both the teaching staff and the affected student, and a new date will be scheduled within the same academic period to make up for the missed evaluation activity.\" Section 1 of Article 264. Calendar of evaluation activities (Academic Regulations UAB).
Students of the Faculty of Economics and Business, who in accordance with the previous paragraph need to change an evaluation activity date must process the request by filling out an Application for exams' reschedule: e-Formulari per a la reprogramació de proves.
Grade revision process
After all grading activities have ended, students will be informed of the date and way in which the course grades will be published. Students will be also be informed of the procedure, place, date and time of grade revision following University regulations.
Retake Process
\"To be eligible to participate in the retake process, it is required for students to have been previously been evaluated for at least two thirds of the total evaluation activities of the subject.\" Section 2 of Article 261. The recovery (UAB Academic Regulations). Additionally, it is required that the student to have achieved an average grade of the subject greater than or equal to 3.5 and less than 5.
The date of the retake exam will be posted in the calendar of evaluation activities of the Faculty. Students who take this exam and pass, will get a grade of 5for the subject. If the student does not pass the retake, the grade will remain unchanged, and hence, student will fail the course.
Irregularities in evaluation activities
In spite of other disciplinary measures deemed appropriate, and in accordance with current academic regulations, \"in the case that the student makes any irregularity that could lead to a significant variation in the grade of an evaluation activity, it will be graded with a 0, regardless of the disciplinary process that can be instructed. In case of various irregularities occur in the evaluation of the same subject, the final grade of this subject will be 0\". Section 11 of Article 266. Results of the evaluation. (UAB Academic Regulations).
This subject/module does not offer the option for comprehensive evaluation.
The completion of assessment activities is subject to the provisions set out in this course guide and in the "Policy of the School of Economics and Business on the Detection of Irregularities during Assessment Activities", which regulates the conditions under which assessment tasks are conducted and the procedures applicable in cases where indications of irregularities are detected. Students are encouraged to consult the policy.
Bibliography
Recommended book:
Stock J.H. & Watson M.W., Introduction to Econometrics. 3 edition , In Spanish: Introducción a la Econometría, Pearson Education. 3 edición
Other books:
Wooldridge, J. M., Introductory Econometrics: A Modern Approach. In Spanish: Introducción a la Econometría, Cengage Learning.
Gujarati, D., Basic Econometrics. 5 ed, 2010. McGraw-Hill. Latest version in Spanish: Econometria. Quarta edició. 2004.
Maddala, G.S., Introduction to Econometrics. 4ed, 2009. Wiley. Latest version in Spanish: Introducción a la econometría, 2ed, 1996. Prentice Hall
Verbeek, M. A Guide to Modern Econometrics. 3ed, 2008. Wiley.
Software
GRETL, R
Course groups and languages
The information provided is provisional until November 30. After this date, you will be able to consult the language of each group through this link. To access the information, you will need to enter the course CODE
| Type of teaching | Group | Language | Semester | Shift |
|---|---|---|---|---|
| (TE) Theory | 1 | Spanish | first semester | morning-mixed |
| (TE) Theory | 8 | English | first semester | morning-mixed |
| (PLAB) Practical laboratories | 8 | English | first semester | morning-mixed |
| (PLAB) Practical laboratories | 11 | Spanish | first semester | morning-mixed |
| (TE) Theory | 51 | Spanish | first semester | afternoon |
| (PLAB) Practical laboratories | 51 | Spanish | first semester | afternoon |