1. Applied Econometrics 1 Vincent Hogan

2. Introduction & Outline
Introduce me
Lectures and Labs
Course material
Course outline and objectives

3. Me Vincent Hogan vincent.hogan@ucd.ie  (716) 8300
Room D205, Newman Building
Office Hours: Mon 10pm-noon or by appointment

4. Lectures and Labs Lectures: Tues & Thurs 10-12 Theatre Q. Labs
Several locations and times
Tues D114 & D115 HEA
Wed G5 DAE
Thurs G5 & G6 DAE
 Labs start in week 2

5. Role of Labs Labs are NOT tutorials in the traditional sense.
The scheduled labs are merely times where the computer labs are reserved for your use exclusively
AND where there will be some support for using the course software provided by Phd Students
You are not obliged to attend labs but Econometrics is a practical subject so you need to practice either in the supervised labs or on your own

6. Course Software
Econometrics is a practical subject that involves the analysis of real world data
We will use software called stata which can be accessed via NAL on the ucd network
You cannot access it at home
There is freeware at gretl.com which will do most of the analysis we need on this course
Neither I nor UCD will offer support for gretl

7. Using Stata Vital to get comfortable with basics in stata
Manuals on the course website
Lots of online help for stata
Practice its use in the labs where the grad students can help you
Stata will be needed for assignments
Understanding the output will be key for class and the final exam

8. Course Website
The course material will be available at
Material will be posted in blog form
Course notes
Example data
Stata comand files
Software manuals
Sample exams
The blackboard site for this course contains the lecture material from previous years.
Not of much relevance

9. Course Material
You are strongly advised to bring a printed copy of these notes to the lecture to enable you to follow the material. 
These notes are not designed to be sufficient on their own.
The recommended text book is
Introductory Econometrics by Jeffrey Wooldridge 
Should be in the campus bookshop
Second hand copies should be fine

10. Alternative Texts
All of these texts should be fine and maybe available second hand
“Basic Econometrics”, Damodar Gujurati, McGraw-Hill
Introduction to Econometrics” by James Stock and Mark Watson,
Modern Econometrics: an introduction”, R L Thomas, Addison-Wesley,
“Introduction to Econometrics”, G.S Maddala, Prentice Hall,
“A Guide to Econometrics”, Peter Kennedy, Blackwell,
“Learning and Practising Econometrics”, Griffith Hill and Judge, John Wiley.

11. Assessment Assessment will be based on
2 pieces of assessed work each worth 10% of the course grade
An end of year exam worth 80%
The projects will involve applying the methods of class to real world data which I will provide.
due at end of week 8 and week 10 
In addition there will be an assignment every week for practice i.e. not for grade
The final exam will be slightly more theoretical but will still have a large practical component

12. Introduction to Econometrics
What is econometrics?
Learning objectives
Method of teaching.

13. What is Econometrics
In a nutshell Econometrics is statistics applied to economic relationships
quantify economic relationships
A simple example:
Keynesian Consumption function
 income today,  consumption today or  savings today
C=a+b*Y
 Another Example Return to Education:
What is  in income from holding a degree

14. Demand for fuel: response of consumer demand to change in excise tax?
How much matters to the government

15. Key Issue: Managing Uncertainty
Economic Theory defines a relationship between variables
Agents require the size of the effects e.g. MPC, elasticity of demands.
Key issue:
Whole population never observed only sample
Creates uncertainty
Managing uncertainty is the key point of statistics

16. Steps in the Analysis Economic Model: state theory or hypothesis
e.g. Keynesian model
Specify a mathematical model: single equation or several.
e.g. C=a+b*Y
Note: 1 & 2 from your other courses
Specify statistical model: how deal with “errors” caused by sampling
This is what makes statistics
Get data: I provide for this course
But for your own project you will need to get data

17. Steps in the Analysis
Estimate the parameters of the model that best fit to the data. e.g. what “b” gives the best fit
Reject the Model?
Test hypotheses regarding the parameters. e.g. is “b” = 0.8?
Not trivial because of sample
Prediction: “What if”
implicit in everything

18. Learning Objectives
Understand how to perform linear regression analysis of economic data to derives estimates of parameters defined by economic theory
Understand how to perform hypothesis tests on the regression results in order to reject (or not) alternative economic theories
Use the results of the analyses to describe the effects of alternative economic policies and actions

19. Teaching This Course Practical approach
Each section will be motivated by a case study
We will analyse real data in class
Address theoretical issues as they arise in each case study
Apply to some other cases
Further applications as homework
You should repeat the data analysis in your own time and do the assignments for practice
Remember only 2 are for grade

20. Teaching This Course
Failure to actually use data yourself will inhibit your learning
Remember 40% of final exam is based on practical interpretation of stata output

21. Cases & Topics Are women paid less than men? What is the MPC?
Intro to statistics
What is the MPC?
Simple regression
How low will house prices fall?
Multivariate regression
Big is beautiful: Asymptotic theory
Mid way review & several examples

22. Cases & Topics What is the return to education?
Omitted variables and errors in variables
What is the elasticity of demand for fuel?
Functional form
Review some of the cases for statistical problems of heteroscedasticity and autocorrelation