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Prof. Gennaro Zezza

Contact information: zezza@unicas.it

Term: Second Semester

Credits (ECTS): 6

Prerequisites: Succesful completion of Applied Statistics. Descriptive statistics; inference; matrix algebra; microeconomics; macroeconomics.

Language of Instruction: English

Class hours: 42



LEARNING OBJECTIVES:

Cognitive / Knowledge skills

  • Learn how to forecast on the basis of past information
  • Learn how to use the data to explore causality nexus
  • Learn how to falsify, or validate, a theory on the basis of empirical evidence

Analytical / Critical Thinking Skills (Oral & Written)

  • Select the appropriate econometric model for the problem at hand
  • Estimate econometric models, with specific references to time series approaches
  • Evaluate the robustness of results of econometric models

 

COURSE DESCRIPTION:

This course aims at introducing the students to econometrics, with special emphasis on time series econometrics. We will start from how to visualize the data for exploratory analysis, focusing on the identification of outliers, trends, seasonality. We next move to the analysis of the multiple regression model, covering the properties of Ordinary Least Squares estimation, and related statistics. Particular attention is given to testing for normality, homoscedasticity, auto-correlation, parameter stability, exogeneity.

In the next part of the course we introduce time series analysis, discussing ARIMA models for forecasting. We next move to multi-variate forecasting using stationary variables (VARS). Finally, we introduce modern econometric techniques for time series analysis: the general-to-specific approach in model specification, cointegration using the Engle-Granger, VECM, and ADL approach.

Particular attention will be given to the problem of parameter identification in structural models.

 

INSTRUCTIONAL FORMAT:

The class will meet for 2 hours (gross of interclass break), twice or three times a week, for a total of 21 sessions. After an introduction aimed at providing the needed background, participants are required to read the materials related to the class and to be prepared prior to coming to class. Classes will consist of a lecture by the instructor, to be followed by a discussion of the main topics and the assigned case. Main points about the materials and all doubts brought up by the students will be addressed by the instructor during the class, or during office hours.

 

TENTATIVE COURSE SCHEDULE:

Week 1 (Wooldridge, chapter 1)
Introduction to the Course
Presentation of the Available materials
Clear Statement of Expected Mutual Requirements
Properties of data sets: surveys (cross-section); time-series; panel
Exploratory analysis: trends, seasonality; outliers
Basic inference: properties of estimators

Week 2 (Wooldridge, chapters 2-3)
Basic inference: test of hypothesis
Matrix algebra: transposition, product, inverse, etc.

Week 3 (Wooldridge, chapters 4-9)
The multiple regression model (OLS)
Assumptions required for optimal properties of the OLS estimator
The distribution of the OLS estimator
The t-test and F test on parameters. The R-square statistics

Week 4 (Wooldridge, chapters 4-9)
Introduction to the Eviews econometric software
Test of hypothesis with the OLS model
Inference and forecasting with the OLS model
The GLS estimator

Week 5 (Enders, chapters 1-2, 4)
Stochastic processes. Stationarity
Test for unit roots

Week 6 (Enders, chapter 2)
ARMA modeling
Forecasting with ARIMA models
Introduction to seasonal ARIMA models

Week 7 (Enders, chapters 5)
VAR models with stationary data

Week 8 (Enders, chapters 6)
Cointegration

Week 9 (Enders, chapters 6)
Error correction models
General-to-specific methodology

Week 10 (Enders, chapters 6)
General-to-specific methodology
Model specification

 

WORKLOAD EXPECTATIONS:

All students are expected to spend at least 2,5 hours of time on academic studies outside of, and in addition to, each hour of class time.

 

FORMS OF ASSESSMENT:

The instructor will use two criteria for assessing your work. Any questions about the requirements should be discussed directly with your faculty well in advance of the due date for each assignment.

 

FORM OF ASSESSMENT

VALUE

Class Participation        

15%

Final Exam

85%

 

 

ASSESSMENT OVERVIEW:

Class Participation:  This grade will be calculated to reflect your participation in class discussions, your capacity to introduce ideas and thoughts dealing with the texts, your ability to use language effectively, and to present your analysis in intellectual, constructive argumentation. If you cannot attend classes your participation can be shown by interacting with your instructor during office hours, i.e. by asking about specific subjects of the syllabus and discussing assignments.

Final Exam: Students will be required to submit a short paper on one assigned topic. Students will need to discuss their paper at the exam, to show they have fully grasped each step of the procedure required to complete the assignment. In order to pass, students need to show their comprehension of all of the aspects of their work (i.e. be able to explain what is being tested, what is the result of a test, what is the implication, etc.)

 

CLASS/INSTRUCTOR POLICIES:

Professionalism and communications: As a student, you are expected to maintain a professional, respectful and conscientious manner in the classroom with your instructors and fellow peers.

You are expected to take your academic work seriously and engage actively in your classes.. Advance preparation, completing your assignments, showing a focused and respectful attitude is expected of all students. Simply showing up for class or meeting minimum outlined criteria will not earn you a good grade in this course. Utilizing communications, properly addressing your faculty and staff, asking questions and expressing your views respectfully demonstrate your professionalism and cultural sensitivity.

Attendance and Classroom behavior: Although attendance is not compulsory, it is highly recommended. All students must have a respectful attitude towards the professor as well as the classmates.

Arriving late / departing early from Class: Once they have decided to attend, students must behave consistently. Arriving late or leaving class early is disruptive and shows a lack of respect for instructor and fellow students.

Make-up classes: The instructor reserves the right to schedule make-up classes in the event of an unforeseen or unavoidable schedule change. Make-up classes may be scheduled outside of typical class hours, as necessary. 

Missing Examinations: Examinations will not be rescheduled. Pre-arranged travel or anticipated absence does not constitute an emergency and requests for missing or rescheduling exams will not be granted.

Use of Cell Phones, Laptops and Other Electronic Devices: Always check with your instructor about acceptable usage of electronic devices in class. Inappropriate usage of your electronic devices will result in a warning and may lead to a deduction in participation grades. Use of a cell phone for phone calls, text messages, emails, or any other purposes during class is impolite, inappropriate and prohibited. You are strongly encouraged to bring your laptop when the class will be engaged in empirical work.

On-line platform: The instructor will use the Moodle platform available on the Unicas website for circulating materials, data sets, etc. Students are expected to register on the platform, register for the course, and check the web page regularly.

 

REQUIRED READINGS:

Listed below are the required course textbooks and additional readings. These are required materials for the course and you are expected to have constant access to them from the very beginning of the course for reading, highlighting and note-taking. It is required that you have unrestricted access to each. Access to additional sources required for certain class sessions may be provided in paper or electronic format consistent with applicable copyright legislation.

Required texts

Wooldridge, Introductory Econometrics: A Modern Approach, Cengage, latest edition

Enders, Applied Econometric Time Series, Wiley, latest edition

Introductory readings:

Before the course starts, students should revise their knowledge of inference (estimators and their properties, test of hypothesis), using any introductory textbook. Students are also expected to revise their knowledge about matrix algebra. A good knowledge of macroeconomics is also required.

Online Reference & Research Tools:

1)      www.time-series.net/

The web site for Enders’ textbook.

2)      www.federalreserve.gov

The Federal Reserve System is the central bank of the United States. It produces most of the statistics we will use for monetary and financial data.

3)      www.bea.gov

The Bureau of Economic Analysis (BEA) produces national account data for the United States, that will be used during classes.

4)      www.bls.gov

The Bureau of Labor Statistics produces data on the labor market, inflation and other topics, that will be used during classes.

5)      http://www.worldbank.com

The World Bank maintains a large database of annual data for all countries in the world on a variety of topics.

6)      http://www.imf.org

The IMF produces time series and projections for all countries on some key economic indicators.

7)      Eurostat

Eurostat collates statistical information for all countries in the European Union.

 

 

 

[Ultima modifica: venerdì 15 settembre 2017]