Semester One Sample Mid-Semester Examinations, 2017
ECON2300 Introductory Econometrics
Semester One Midsemester Examinations, 2013
Semester One Final Examinations, 2013
ECON7002 Economics for Commerce
ECON7150 Mathematical Techniques for Economics
Semeste
Please note that LIFT does not warrant the correctness of the materials contained within the notes. Additionally, in some cases, these
notes were created for previous semesters and years. Courses are subject to change over time, both in content and scope
Please note that LIFT does not warrant the correctness of the materials contained within the notes. Additionally, in some cases,
these notes were created for previous semesters and years. Courses are subject to change over time, both in content and scope
Please note that LIFT does not warrant the correctness of the materials contained within the notes. Additionally, in some cases, these
notes were created for previous semesters and years. Courses are subject to change over time, both in content and scope
Please note that LIFT does not warrant the correctness of the materials contained within the notes. Additionally, in some cases, these
notes were created for previous semesters and years. Courses are subject to change over time, both in content and scope
Please note that LIFT does not warrant the correctness of the materials contained within the notes. Additionally, in some cases, these
notes were created for previous semesters and years. Courses are subject to change over time, both in content and scope
Please note that LIFT does not warrant the correctness of the materials contained within the notes. Additionally, in some cases, these
notes were created for previous semesters and years. Courses are subject to change over time, both in content and scope
Please note that LIFT does not warrant the correctness of the materials contained within the notes. Additionally, in some cases, these
notes were created for previous semesters and years. Courses are subject to change over time, both in content and scope
Please note that LIFT does not warrant the correctness of the materials contained within the notes. Additionally, in some cases, these
notes were created for previous semesters and years. Courses are subject to change over time, both in content and scope
Please note that LIFT does not warrant the correctness of the materials contained within the notes. Additionally, in some cases, these
notes were created for previous semesters and years. Courses are subject to change over time, both in content and scope
Please note that LIFT does not warrant the correctness of the materials contained within the notes. Additionally, in some cases,
these notes were created for previous semesters and years. Courses are subject to change over time, both in content and scope
Please note that LIFT does not warrant the correctness of the materials contained within the notes. Additionally, in some cases, these
notes were created for previous semesters and years. Courses are subject to change over time, both in content and scope
Please note that LIFT does not warrant the correctness of the materials contained within the notes. Additionally, in some cases, these
notes were created for previous semesters and years. Courses are subject to change over time, both in content and scope
ECON2300 L1
Economics and Econometrics
Econometrics deals with tools employed in the business disciplines of
accounting, finance, marketing and management.
It is fundamental for economic measurement
It applies statistical procedures to problems i
ECON2300
Autocorrelation
Eric Eisenstat
Week 7
1 / 31
In this lecture
What is Autocorrelation
Properties of the OLS Estimator
Detecting Autocorrelation
OLS and GLS Estimation
Next Week
2 / 31
What is Autocorrelation
Properties of the OLS Estimator
Detecti
QUESTION 1
Your model has a heteroskedastic error term, but you do not know the
functional form of the variance equation. What should be done?
a. Use Whites Robust Estimator of Standard Errors.
b. Add observations to the dataset and estimate again.
c. Try
Online Assignment 1
1. Economic theory provides a basis for which variables are relevant and
should be included in an econometric model. But econometrics provides tools
to estimate _ which tells us
_.
a. a model, the functional form that should be used
b.
Todays Topics:
ECON1310
Simple Linear Regression (SLR) Continued
(Chapter 13)
Quantitative Economic & Business Analysis A
LECTURE 12
Simple Linear Regression Part 2
1 hour of online YouTube videos on Blackboard
to be viewed to complete Lecture 12
1
The Es
Feedback (from Lecture 8)
ECON1310
Quantitative Economic & Business Analysis A
The confidence interval would be
narrower if:
a) the sample was larger
LECTURE 9
Hypothesis Testing Part 1
1 hour of online YouTube videos on Blackboard
to be viewed to complet
Feedback (from Lecture 7)
ECON1310
Quantitative Economic & Business Analysis A
LECTURE 8
Estimation using Confidence Intervals Part 2
When we read about the results of surveys or
polls, there is often a statement regarding the
precision. For example, the
Lecture 6 Feedback.
ECON1310
Quantitative Economic & Business Analysis A
Consider: A car magazine stated that 70% of all new
car buyers also bought a 5-year extended warranty.
From a random sample of 60 new car buyers, there
were 42 buyers who did purchas
Todays lecture
ECON1310
Quantitative Economic & Business Analysis A
Key probability concepts (Ch 4.1 4.2)
experiment, trial, event, sample space, union and
intersection, and events that are independent, mutually
exclusive, collectively exhaustive, and co
Todays lecture
Section 5.1 5.2
Discrete probability distributions
probability calculations
graphical presentation
mean (expected value), standard deviation
ECON1310
Quantitative Economic & Business Analysis A
Section 5.3
Binomial distribution (specific
Todays Topics:
Simple Linear Regression (SLR), Chapter 13
What is it? Why is it used?
The link with correlation.
Estimation (using Excel and not hand calculation).
Interpretation of Excel analysis results.
ECON1310
Quantitative Economic & Business Analys
Please note that LIFT does not warrant the correctness of the materials contained within the notes. Additionally, in some cases, these
notes were created for previous semesters and years. Courses are subject to change over time, both in content and scope
Please note that LIFT does not warrant the correctness of the materials contained within the notes. Additionally, in some cases, these
notes were created for previous semesters and years. Courses are subject to change over time, both in content and scope
ECON2300 Brief Guide to Solution for Week 3
SIMPLE LINEAR REGRESSION B
1. Scale
a)
x =
x
10
b)
y =
y
10
c)
y =
y
x
; x =
10
10
R2 remains the same in each case
2. Houses
(a) The EViews command:
Quick Graph
series name = SQFT PRICE Select scatter as graph
ECON2300 Brief Guide to Tutorial Solution for
MULTIPLE LINEAR REGRESSION B
1. Rice
The EViews command:
Quick Estimate Equation
Log(prod) c log(area) log(labour) log(fert)
(a) Re-estimate
i. The EViews command:
Quick Estimate Equation
Log(prod) c log(are
ECON2300
Simple Regression A
Alicia N. Rambaldi
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
Next We