ECON 7310: ELEMENTS OF ECONOMETRICS
Tutorial 1: EViews and Basic Statistics
At the end of this tutorial you should be able to
Q1.
use EViews to read, manipulate and save data and workfiles
use EViews to compute descriptive statistics
use EViews to conduct
ECON7310 Tutorial Exercises for Week 7
HETEROSKEDASTICITY
At the end of this tutorial you should be able to
Q1.
define heteroskedasticity and give examples of econometric models where heteroskedasticity is likely to
exist;
examine residual plots for heter
ECON 7310: ELEMENTS OF ECONOMETRICS
Dr. Dong-Hyuk Kim
Tutorial 1: Stata and Basic Statistics
At the end of this tutorial you should be able to
use Stata to read, manipulate and save data and workfiles
use Stata to compute descriptive statistics
use Sta
ECON 7310: ELEMENTS OF ECONOMETRICS
Dr. Dong-Hyuk Kim
Tutorial 2: Simple Linear Regression, Part A
At the end of this tutorial you should be able to
understand and explain the assumptions behind the simple linear regression model;
explain the properties
ECON 7310: ELEMENTS OF ECONOMETRICS
Dr. Dong-Hyuk Kim
Tutorial 4: Multiple Linear Regression, Part A
At the end of this tutorial you should be able to
understand and explain the assumptions behind the multiple regression model;
explain the properties of
ECON 7310: ELEMENTS OF ECONOMETRICS
Dr. Dong-Hyuk Kim
Tutorial 3: Simple Linear Regression, Part B
At the end of this tutorial you should be able to
use the estimated regression model to generate predictions;
compute and interpret the coefficient of det
ECON 7310: ELEMENTS OF ECONOMETRICS
Dr. Dong-Hyuk Kim
Tutorial 2: Simple Linear Regression, Part A
At the end of this tutorial you should be able to
understand and explain the assumptions behind the simple linear regression model;
explain the properties
ECON 7310: ELEMENTS OF ECONOMETRICS
Dr. Dong-Hyuk Kim
Tutorial 3: Simple Linear Regression, Part B
At the end of this tutorial you should be able to
use the estimated regression model to generate predictions;
compute and interpret the coefficient of det
ECON 7310: ELEMENTS OF ECONOMETRICS
Dr. Dong-Hyuk Kim
Tutorial 1: Stata and Basic Statistics
At the end of this tutorial you should be able to
use Stata to read, manipulate and save data and workfiles
use Stata to compute descriptive statistics
use Sta
ECON 7310: Principles of Econometrics
Model Mid-Semester Examination
PART A
Multiple Choice Questions
(30 marks)
1. Under the standard assumptions of the simple regression model, yi 1 2 xi ei where
x is non-stochastic, the OLS estimator of the slope coeff
ECON7310 ELEMENTS OF ECONOMETRICS
Tutorial 2: SIMPLE LINEAR REGRESSION A
At the end of this tutorial you should be able to
Q1.
understand and explain the assumptions behind the simple linear regression model;
explain the properties of the least squares es
ECON7310 Tutorial Exercises for Week 3
SIMPLE LINEAR REGRESSION B
At the end of this tutorial you should be able to
Q1.
use the estimated regression model to generate predictions;
compute and interpret the coefficient of determination;
describe how the es
ECON7310: ELEMENTS OF ECONOMETRICS
Tutorial Exercises for Week 4: MULTIPLE REGRESSION A
At the end of this tutorial you should be able to
understand and explain the assumptions behind the multiple regression model;
explain the properties of the least squa
ECON7310 Tutorial Exercises for Week 5
MULTIPLE REGRESSION B
At the end of this tutorial you should be able to
Q1.
explain the consequences of omitted and irrelevant variables for the properties of the least squares estimator;
explain the term multicollin
ECON7310 Tutorial Exercises for Week 6
MULTIPLE REGRESSION B/ DUMMY VARIABLES
At the end of this tutorial you should be able to
explain how to incorporate intercept and slope dummy variables into a regression model;
identify the reference group in a dum
ECON7310 Practical Exercises for Week 10
NON-STATIONARITY
At the end of this tutorial you should be able to:
explain the difference between stationary and nonstationary processes;
explain the difference between, and give examples of, trend-stationary an
ECON7310 Tutorial Exercises for Week 8
AUTOCORRELATION
At the end of this tutorial you should be able to
define autocorrelation and give examples of econometric models where autocorrelation is likely to exist;
examine residual plots and correlograms for
ECON7310 Tutorial Exercises for Week 9
DYNAMIC MODELS
At the end of this tutorial you should be able to
Q1.
estimate an autoregressive model and use it to obtain forecasts;
specify, estimate and interpret estimates of a finite distributed lag model;
compu
ECON 7310: ELEMENTS OF ECONOMETRICS
Dr. Dong-Hyuk Kim
Tutorial 4: Multiple Linear Regression, Part A
At the end of this tutorial you should be able to
understand and explain the assumptions behind the multiple regression model;
explain the properties of
ECON2300/7310
Simple Regression A
Taya Dumrongrittikul
Week 2
1 / 39
In this lecture
The Simple Regression Model
Least Squares Estimation
Properties of the LS Estimators
Estimating the Variances of the LS Estimators
Interval Estimation
Hypothesis Testing
Week 1 Introduction
2
ECON 7310 Tutorial 1: Solutions
Q1.
a)
The main EViews commands:
File Open Foreign Data as Workfile .
b) The EViews command:
CONS
Quick Graph
series name = INC
Select scatter as graph type
The EViews results:
1,000
800
600
400
200
0
Student Name: Dongyu Wei
Student Number: 43392917
Assignment
Question a) In our database analysis, BHP and return is the positive relationship revealed by the
scatter plot confirms this. Coles Myer and return is also the positive relationship revealed by
Student Name: Dongyu Wei
Student Number: 43392917
Assignment
1. For variable SQFT, the average of house size is 2335.929 total square feet. The
maximum of all house size is 7897 total square feet. The minimum of all house size is
720 total square feet. Fo
vacation.def
miles income age kids
Obs: 200
1. miles miles traveled per year
2. income annual income in $1000's
3. age average age of adult members of household
4. kids number of children in household
A sample of Chicago households.
Variable |
cloth.def
c1 q1 c2 q2
Obs: 28 annual time series observations on two clothing firms
c1 total cost for firm 1
q1 output for firm 1
c2 total cost for firm 1
q2 output for firm 1
Variable | Obs Mean Std. Dev. Min Max
-+-
c1 | 28 346.3929 143.989
rice.def
firm year prod area labor fert
Obs: a panel with 44 firms over 8 years (1990-1997)
total observations = 352
firm Firm number ( 1 to 44)
year Year = 1990 to 1997
prod Rice production (tonnes)
area Area planted to rice (hectares)
labor H
MakingaGreatPresentation
SabrinaTabassum
TheUniversityofQueensland
PresentationOverview
Beforeyoustart:Plan
vDetermine the objective of your talk
vConsider the your target audience
Expectations
Age
Knowledge of the topic
vConsider the presentation leng