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2015/2016  BA-BHAAI1044U  An introduction to econometrics

English Title
An introduction to econometrics

Course information
Language English
Course ECTS 7.5 ECTS
Type Elective
Level Bachelor
Duration Summer
Start time of the course Summer
Timetable Course schedule will be posted at calendar.cbs.dk
Study board
Study Board for BSc in Economics and Business Administration
Course coordinator
  • Course instructor - Dr Rene Ordonez
    Sven Bislev - MSC
Main academic disciplines
  • Management
  • Statistics and quantitative methods
  • Economics
Last updated on 10/08/2017
Learning objectives
To achieve the grade 12, students should meet the following learning objectives with no or only minor mistakes or errors:
  • Demonstrate a broad comprehension of terms, concepts, theories, and processes in econometric models and tools.
  • Identify the proper econometric technique to apply to a problem or data set.
  • Apply the appropriate econometric technique using an appropriate software to solve economics and business-related problems.
  • Interpret properly the results of econometric analysis, including recognizing pitfalls and problems encountered in undertaking applied modelling.
Course prerequisites
Required: Basic algebra, working knowledge of spreadsheet application (Excel), and successful completion of any introductory statistics course that would provide coverage of foundational concepts of statistics including probability distributions and the basics of parametric estimation.
Prerequisites for registering for the exam
Number of mandatory activities: 1
Compulsory assignments (assessed approved/not approved)
The examination is mandatory. A feedback activitity defined by the course instructor will take place app. half-way through the course.
A preliminary assignment, to be completed before arrival, is offered to fulfil the 7.5 ECTS.
Examination
An introduction to econometrics:
Exam ECTS 7.5
Examination form Written sit-in exam
Individual or group exam Individual
Assignment type Written assignment
Duration 4 hours
Grading scale 7-step scale
Examiner(s) One internal examiner
Exam period Summer, Ordinary exam: 1-5 August 2016
Retake exam: Within two months from the ordinary exam.
Aids allowed to bring to the exam Open book: all written and electronic aids, including internet access
Make-up exam/re-exam
Same examination form as the ordinary exam
If the number of registered candidates for the make-up examination/re-take examination warrants that it may most appropriately be held as an oral examination, the programme office will inform the students that the make-up examination/re-take examination will be held as an oral examination instead.
a 4 hour written sit-in exam, with a new exam question
Course content and structure

Econometrics is a sub-discipline of economics and statistics that provides methods for inferring economic structure from data. This course has two goals. The first goal is to give students the means to evaluate an econometric analysis critically and logically. The second goal is to give students theh skills to analyze a data set methodically and comprehensively using the tools of econometrics. Students will be introduced to simple and multiple regression methods for analyzing data in economics and related disciplines. Extensions will include regression with discrete random variables, analysis of qualitative questions, interaction terms and binary choice models. The course will also explore the use of time series analysis as a forecasting technique.

 

The course will be delivered via a combination of lectures and problem-solving, requiring students to apply advanced statistical models and techniques (econometrics) to business and economics-related problems. Computer-based statistical tools (Excel and STATA) are utilized in tackling problem solving. 

The course is designed to meet and satisfy the learning standards on quantitative analysis required by international business schools accrediting bodies such as the Association to Advance Collegiate Schools of Business (AACSB) and the Accrediting Council for Business Schools and Programs (ACBSP).

 

For the Preliminary Assignment students are to download the Excel Statistical Interaction Template and watch a video on the use of the template in preparation for an assignment using it to be completed by the end of the day of Class 1. The Feedback Activity will be ...

 

Class

Topic

Class 1

Preliminary Assignment (outside class activity)

Review of Basic Statistics Concepts – Distributions

Class 2

Hypothesis Testing Concepts Review

Class 3

Simple Linear Regression (SLR) – Scatterplots, Basic terms and concepts, Model-building

Class 4

Simpe Linear Regression – Hypothesis Testing, Estimation

Class 5

Issues in SLR Model Building – Autocorrelation, Lack of Fit, Heteroscedasticity, Variable Transformation, Durbin-Watson Test

Class 6

Feedback Activity

Class 7

Multiple Linear Regression (MLR)- Basic concepts

Class 8

Multiple Linear Regression – Models with Qualitative Variables

Class 9

Multiple Linear Regression – Issues in MLR Model-building (multicollinearity, lack-of-fit, omitted and irrelevant variables, etc.)

Class 10

Time Series Modeling and Forecasting (time permitting)

Class 11

Comprehensive Review
Teaching methods
Essentially, the learning environment will follow the Confucian learning philosophy: “Tell Me and I Will Forget; Show Me and I May Remember; Involve Me and I Will Understand.”

The course will be a combination of lectures, situational problem solving and case analysis. Lectures will address the concepts and proper procedures for carrying out the various econometric models and tools covered in the class. This will be followed by application of the concepts and methods to business and economic-related problems. Computer software, mainly Excel and SPSS, will be used in solving statistical problems.

Students will be expected to read the assigned material and work on assigned textbook problems outside of class. The assigned textbook problems are not for submission. An Excel-based statistical template developed by the instructor will be used as a class supplement. Digitized lectures (e.g., digitally recorded computer-based lectures and demos) will also be made available to students via LEARN to further enhance learning.
Further Information

Preliminary Assignment: To help students get maximum value from ISUP courses, instructors provide a reading or a small number of readings or video clips to be read or viewed before the start of classes with a related task scheduled for class 1 in order to 'jump-start' the learning process.

 

The timetable is available on http://
Expected literature

Required:

Practical Econometrics: Data Collection, Analysis and Application (2014)

Authors: Hilmer, Christiana; Hilmer, Michael

Publisher: McGraw-Hill Higher Education

ISBN 9780071318518 (paperback)

 

Optional:

Small Stata (software for student use – 6 month license $35)

http://www.stata.com/order/new/edu/gradplans/student-pricing/

 

Additionally, a set of Supplemental Lecture Notes (possibly 50 to 100 pages) created by the instructor will be available to students. The Notes will be in electronic format provided to the student free of charge via LEARN.

 
Last updated on 10/08/2017