ECON 30130 - Vincent Hogan`s Blog

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ECON 30130
Applied Econometrics 1
Vincent Hogan
Introduction & Outline
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Introduce me
Lectures and Labs
Course material
Course outline and objectives
Me
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Vincent Hogan
[email protected]
 (716) 8300
Room D205, Newman Building
Office Hours: Mon 10pm-noon or by
appointment
Lectures and Labs
• Lectures: Tues & Thurs 10-12 Theatre Q.
• Labs
– Several locations and times
– Tues 17.00-1900 D114 & D115 HEA
– Wed 17.00-19.00 G5 DAE
– Thurs 18.00-20.00 G5 & G6 DAE
• Labs start in week 2
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
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
Using Stata
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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
Course Website
• The course material will be available at
www.vincenthogan.ie
• Material will be posted in blog form
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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
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
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.
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
Introduction to Econometrics
• What is econometrics?
• Learning objectives
• Method of teaching.
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
• Demand for fuel:
– response of consumer demand to change in excise
tax?
– How much matters to the government
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
Steps in the Analysis
1. Economic Model: state theory or hypothesis
e.g. Keynesian model
2. Specify a mathematical model: single equation
or several.
–e.g. C=a+b*Y
–Note: 1 & 2 from your other courses
3. Specify statistical model: how deal with “errors”
caused by sampling
– This is what makes statistics
4. Get data: I provide for this course
– But for your own project you will need to get data
Steps in the Analysis
5. Estimate the parameters of the model that
best fit to the data. e.g. what “b” gives the
best fit
6. Reject the Model?
– Test hypotheses regarding the parameters. e.g. is
“b” = 0.8?
– Not trivial because of sample
7. Prediction: “What if”
– implicit in everything
Learning Objectives
1. Understand how to perform linear regression
analysis of economic data to derives estimates
of parameters defined by economic theory
2. Understand how to perform hypothesis tests on
the regression results in order to reject (or not)
alternative economic theories
3. Use the results of the analyses to describe the
effects of alternative economic policies and
actions
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
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
Cases & Topics
1. Are women paid less than men?
– Intro to statistics
2. What is the MPC?
– Simple regression
3. How low will house prices fall?
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Multivariate regression
4. Big is beautiful: Asymptotic theory
5. Mid way review & several examples
Cases & Topics
6. What is the return to education?
– Omitted variables and errors in variables
7. What is the elasticity of demand for fuel?
– Functional form
8. Review some of the cases for statistical
problems of heteroscedasticity and
autocorrelation

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