Introductory Econometrics

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EC313
Introductory Econometrics

Introduction

Welcome to EC313 Introductory Econometrics. This five-credit, course uses statistical tools to estimate and test business and economic models. The prerequisite for this course is some basic knowledge of statistics and economics. The course emphasizes both theories and applications. There are six units in this course. Each unit takes about two to six weeks to finish, and the whole course takes approximately 20 weeks to complete. Students are expected to spend around ten hours a week studying this course.

What this course helps you do

This introductory sections sets out the major aims and objectives for EC313. You should read them carefully, and come back to them from time to time as you work through the course so that you can give yourself a 'check-up' -- that is, to see if you are meeting these aims and objectives.

Aims

This course deals with quantitative model building and statistical skills which you will find useful in economics, marketing, risk management, and investment. It aims to teach you how to use statistical techniques to estimate and test in business and economics. You will learn how to create a statement of theory or a hypothesis, how to collect data, and how to specify economic and business models. You will also learn how to estimate the parameters of your chosen forecasting model, check for model adequacy, and test the hypotheses derived from the model.

Objectives

After completing this course, you should be able to:

1. Familiarize yourself with some commonly used probability distribution.

2. Test simple statistical hypotheses.

3. Use regression models to analyse business and economic data including cases when data are not quantifiable, e.g. gender, seasons, brand loyalty.

4. Understand the more advanced model building technique such as the simultaneous equation system and logit model.

5. Evaluate the models.

Course materials

This practical topic sets out the materials you'll need for your study of EC313; in particular, it introduces you to the course's six study units.

In addition to this Course Guide, the course has the following important components. Please ensure that you have all of these materials available.

Study units

The study units are listed and briefly described below.

• Unit 1 The nature of econometrics and description of major economic data

This unit introduces you to the basic concepts related to research methods in economics and business forecasting. The essential skills in using a related computer software package, Econometrics Views (EViews) are also introduced. The unit then describes some major sources of economic data, especially those from Hong Kong. Some important Hong Kong economic data such as GDP, inflation rate and unemployment rate are also described.

• Unit 2 A review of the basics in statistics

This unit helps you review the basic statistical skills. You will learn what a random variable is, and how to differentiate between a discrete random variable and a continuous random variable. You will also learn how to calculate the mean and the variance of a random variable. The unit then briefly discusses some important distributions and theorems in statistics, and the standard procedures for hypothesis testing.

• Unit 3 The simple linear regression model

This unit discusses the basic ideas underlying linear regression in terms of a two-variable model. You will learn to distinguish between population regression and sample regression, and to estimate a regression model by the method of least squares, which is one of the most popular methods of estimation. You'll also be introduced to the principle of the least squares procedure and learn to apply it to estimate the simple linear regression model. You will then learn to perform hypothesis testing on the linear regression model, and to use the regression model to make simple statistical predictions.

• Unit 4 Multiple regression models

This unit focuses on multiple regression, which relates a given dependent variable to several independent variables. You will learn how to estimate and perform hypothesis testing related to a multiple regression model. In particular, you will learn how to choose the functional forms of regression models. The unit also discusses the problems of multicollinearity, heteroscedasticity and serial correlation in multiple regression.

• Unit 5 Model selection and introduction to simultaneous equations

This unit consists of two parts. The first part focuses on issues related to model selection, including discussion of the types of specification errors and their consequences. You will also learn the procedure for detecting specification errors. The second part of the unit comprises a brief discussion of the simultaneous equations model. You will study the nature of the model and the procedure for estimating the model.

• Unit 6 Qualitative variables in regression models

The variables of the linear regression models in the previous units are numerical or quantitative. There are occasions, however, where variables can be qualitative in nature. When the independent variable is qualitative, it is often known as a 'dummy variable'. In this unit, you learn how to estimate a regression model with dummy variables and correctly interpret the regression results. This unit also includes a brief discussion of regression models when the dependent variable is qualitative.

In each unit there are self-test questions and practice exercises. Most of these questions are selected from your textbook and the accompanying instruction manual. Make sure that you attempt all the questions to check that you understand the study units.

Some of the data in the study units are formatted in electronic form, with the data presented as excel files. To access the data files, go to the Online Learning Environment (OLE) at http://ole.ouhk.edu.hk. Click on EC313 --> Course Materials --> Data Files. You can download the Excel files to work on it.

Textbooks

There are two textbooks for this course:

1. Gujarati, D (2006) Essentials of Econometrics, 3rd edn, McGraw-Hill.

2. Asteriou, D and Hall, S G (2007) Applied Econometrics, A Modern Approach (rev. edn), Macmillan.

Assignment

There will be three Tutor-marked Assignments.

Presentation Schedule

The Presentation Schedule included in the course materials gives the dates for completing TMAs, and attending tutorials, and so on.

Assessment

Self-tests

The self-tests in the study units provide a means for self-assessment. They help you better understand the key concepts in the units and check your progress.

Tutor-marked Assignments

There are three assignments but only the best two of the three assignments will be counted in your final grade:

• Assignment 1 covers the material in Units 1-2.

• Assignment 2 covers the material in Units 3-4.

• Assignment 3 covers the material in Units 5-6.

Each assignment consists of a problem set and/or computer exercise. Your tutor will assess the TMAs in the Assignment File.

Final examination and grading

The final exam will cover all the materials studied in the course. It carries the weight of 50% of the final grade. You will have to answer all the questions in this three-hour closed-book examination. The questions will be similar to those in the assignments and in the exercises provided at the end of each study unit. Some useful formulas will be provided. You will need to bring a calculator and be prepared to read statistical tables.

Note that you will also receive a specimen examination well before you must sit the actual exam, so you will have a good chance to prepare.

Your final grading

Assessment type	Marks
Assignments	25% × 4 = 50%
Examination	50%
Total	100%

Study schedule

The table below is a study schedule for this course:

Unit	Title	Weeks	Assessment activity (end of unit)
1	The nature of econometrics and description of major economic data	2
2	A review of the basics in statistics	3	Assignment 1
3	The simple linear regression model	4
4	Multiple regression models	4	Assignment 2
5	Model selection and introduction to simultaneous equations	4
6	Qualitative variables in regression models	3	Assignment 3

How to get the most from this course

To get the most from this course, you must put serious effort in studying. First, you must read through each study unit and the readings as indicated in the units. The exercises at the end of each unit are not the maximum but the minimum requirement for mastering the material covered in this course. As some of the exercises are demanding, you are strongly recommended to attend tutorials and raise questions whenever you have them. As EC313 is a one-semester, you should make up a study plan, such as spending ten hours a week consistently. Whenever you are stuck, tired, or feel bored with the materials, stop studying and take a break. After you get enough relaxation, go back to the materials to point at which you were stuck, and start thinking them over. Remember, do not make yourself scared of the course, make studying fun and interesting.

Another crucial way to make your study of this course successful is to do more practice exercises. The self-test questions and practical problems in the study units are very useful to help you to understand the key concepts as well as to check your progress. Don't just look at the questions and go directly to the answers. You may find the answer simple, but when you close the book, you will not be able to do the question yourself.

Do not be scared by the mathematics required in EC313. In fact, what you need is nothing more than secondary school mathematics. In addition, there will be a certain number of computer-assisted exercises in this course. Although the Open University provides the required computation facilities on campus, you are advised to have a personal computer of your own installed with Windows 95 at the very minimum or, even better, more advanced versions such as Windows 2000 or XP.

Tutor and tutorials

You will be assigned a tutor for the course. Your tutor is responsible for answering questions raised by students during the tutorial sessions, on the telephone, and via email. Your tutor will also mark your assignments and explain the assignment answers to you. He or she will also be prepared to guide you in the computing part of the course, and will instruct you in how to run regressions using the computer software included with your textbook.

This course provides 14 hours of tutorials. Each study unit usually requires 2-4 hours of tutorials. Again, attending and participating in tutorials is strongly encouraged.

A note about the developer of this course

The course developer, Dr Chan Chi Shing, is a PhD from University of California, San Diego. He was a research economist with the University of Hong Kong University.