ECON0701/2280 Introductory Econometrics
Tutorial 10
1. (Chapter 5, Problem 2)
Suppose that the model
pctstck = 0 + 1 f unds + 2 risktol + u
satisfies the first four Gauss-Markov assumptions, where pctstck is the percentage of a workers
pension invested in

Q1.
(a) Degree of freedom = n k 1 = 33 3 1 = 29
Critical t score
c0.025 = 2.045
95% CI for F = 733 2.045 * 253 = 215.615 to 1250.385
This is statistically significant at 5% since the interval does not include 0.
(Check: computed t = 733/253 = 2.89 > 2.045

Assignment 2 (Total points: 52)
1. This assignment is due by 9:00 AM, March 18 (Wednesday). Please put it in my
TAs assignment locker on 9/F of KKL Building.
2. You can do this assignment individually or with another student from subclasses
F or G taught

Q1.
(a) Please see the STATA output file. In a plot of residuals on total expenditure, the absolute
value of the residuals increases, suggesting the presence of heteroscedasticity.
(b) Please see the STATA output file. The LM statistics from White test is

ECON0701/2280 Introductory Econometrics
Answers for Assignment 1
10
( y i ^ 0 ^ 1 x i 1 ^ 2 x i 2)2
1. (a) Let SSR=
i=1
y i ^0 ^ 1 x i 1 ^ 2 x i 2
()=0 (1)
10
SSR
=
^0 i=1
y i ^0 ^ 1 x i 1 ^ 2 x i 2
x i1 ()=0 (2)
10
SSR
=
^1 i=1
y i ^ 0 ^ 1 x i 1 ^

Assignment 3 (Total points: 58)
1. This assignment is due by 9:00 AM, April 15 (Wednesday). Please put it in the TAs assignment
locker on 9/F of KKL Building.
2. You can do this assignment individually or with another student from subclasses F or G taught

Assignment 1 (Total points: 66)
1. This assignment is due by 10:00 am, February 27, (Monday). Please put it in Felixs
assignment locker on 9/F of KKL Building.
2. This is a group assignment with group size of 2 to 3 students. Your teammates must be
studen

Assignment 4 (Total score: 50 points)
1. This assignment is due by 9 AM on Wednesday, April 29, 2015. Please put it in my
TAs assignment locker on 9/F of KKL Building.
2. You can do this assignment alone or with another student. Hand in one assignment wit

Assignment 1 (Total points: 52)
1. This assignment is due by noon, March 3 (Tuesday). Please put it in my
TAs assignment locker on 9/F of KKL Building.
2. You can do this assignment individually or in a group of 2 students.
You can work with anyone in the

Assignment 1 (Total points: 66)
1. This assignment is due by 10:00 am, February 27, (Monday). Please put it in Felixs
assignment locker on 9/F of KKL Building.
2. This is a group assignment with group size of 2 to 3 students. Your teammates must be
studen

Econ2280 HW 1
Yeung Simon Chun Kin 3035190933 Mon 330-420PM
Iu San San
3035197606 Tue 330-420PM
Lee Kai Sum
3035189922 Mon 330-420PM
1a)
Let TF i = 0+ 1 BEER i + 2 HWSPi + 3 VSIPi + 4 BE E Ri ALT i
TF i
= 1+ 4 ALT i
BEERi
TFi
= 4 BEER i
ALT i
The coef

Midterm Examination
Date:
Saturday, March 21
Time:
4:30 - 6:00 PM
Venue:
KK201, KK202 (A seating plan will be posted in Moodle soon)
Coverage:
Lectures 1 to 5
Related readings:
Chapters 1 to 4, Chapter 6, only pages 193 to top of 197 (about R-squared
and

Econometrics Assignment 1
Question 1a)
First order condition 1
n
n
SSR
^0
u i2
^0 i=1
o ^1 x 1 i ^2 x 2 i )2
( y i ^
i=1
2( y i ^o ^
1 x1 i ^
2 x 2i )(1)
^0
n
2
^
^
^
( y i o 1 x 1i 2 x 2 i)
^
0
i=1
n
2ui
n
i=1
i=1
At the global minimum of SSR,

Formula Sheet
1. In the simple linear regression,
e m WW 3% m and e m :2- we,
where SSTx = 2(3:z 5:")2.
2.
iwo+$31tdi=mm
3' 177(3) 32 admepgzx?
a 1 33:11; E 7" 0 ESSI;
Where 32 = EE/(n 2).
4.
R2_SSE_1_SSR
SST SST
where SST = SSE "5 33R, SST = sz - m2,

Assignment I
Due at 5:30pm of March 3 (Friday)
This assignment is related to Chapter 1 and 2. You can use any formula taught in class without
proof. If you want to use any result from other courses, please provide proof or justication.
Throughout this ass

Assignment II
Due at 5:30pm of April 3 (Monday)
This assignment is related to Chapter 3 and 4. You can use any formula taught in class without
proof. If you want to use any result from other courses, please provide proof or justication.
Note: You need to

Assignment 3 (61 points)
1. This assignment is due by 10:00 am, December 1 (Thursday). Please put it in Felixs
assignment locker on 9/F of KKL Building.
2. This is a group assignment with group size of 2 to 3 students. Your teammates can be
anyone from su

Assignment 1 (Total points: 70)
1. This assignment is due by 8:00 pm, October 14, (Friday). Please put it in Felixs
assignment locker on 9/F of KKL Building.
2. This is a group assignment with group size of 2 to 3 students. Your teammates can be
anyone fr

Answer Key to Tutorial 6
Question 1 (Chapter 4, Problem 6)
(i) With df = n 2 = 86, we obtain the 5% critical value from Table G.2 with df = 90.
Because each test is two-tailed, the critical value is 1.987. The t statistic for H0:
=
0
0 is about -.89, whic

Answer Key to Tutorial 9
Question 1 (Chapter 8, Problem 2)
Var(u|inc,price,educ,female) = 2inc2, h(x) = inc2,
where h(x) is the heteroskedasticity function defined in equation (8.21).
Therefore,
= inc, and so the transformed equation is obtained by
h( x)

Assignment 1 (Total points: 50)
1. This assignment is due by 9:00 am, November 11, (Friday). Please put it in Felixs
assignment locker on 9/F of KKL Building.
2. This is a group assignment with group size of 2 to 3 students. Your teammates can be
anyone f

Answer Key to Tutorial 8
Question 1 (Chapter 7, Computer Exercises C2)
(i) The estimated equation is
The coefficient on black implies that, at given levels of the other
explanatory variables, black men earn about 18.8% less than nonblack
men. The t statis

Answer Key to Tutorial 9
Question 1 (Chapter 8, Problem 2)
Var(u|inc,price,educ,female) = 2inc2, h(x) = inc2,
where h(x) is the heteroskedasticity function defined in equation (8.21).
Therefore,
= inc, and so the transformed equation is obtained by
h( x)

Lecture 3 worksheet
Partialling Out interpretation of OLS coefficients
Consider
^ 1
in
y i= ^ 0 + ^ 1 x i 1+ ^ 2 xi 2
+ . +
^ k x ik + u^ i
1. Regress x1 on all other indep vars x2, x3, , xk, and let the residuals be
x i1 =^ 0+ ^ 2 x i2 + ^ 3 xi 3 + + ^ k

Answer Key to Tutorial 7
Question 2 (Chapter 6, Computer Exercises C7)
(i) If we hold all variables except priGPA fixed and use the usual approximation
(priGPA2) 2(priGPA)priGPA, then we have
stndfnl 2 priGPA 4 ( priGPA2 ) 6 ( priGPA)atndrte
( 2 2 4 priG

The Simple Regression Model
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SLR
1 / 70
Definition of the Simple Regression Model
Definition of the Simple Regression Model
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SLR
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Definition of the Simple

Basic Regression Analysis with Time Series Data
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Basic Time Series
1 / 50
The Nature of Time Series Data
The Nature of Time Series Data
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Basic Time Series
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Multiple Regression Analysis: Inference
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MLR: Inference
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Sampling Distributions of the OLS Estimators
Sampling Distributions of the OLS Estimators
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MLR: In

Multiple Regression Analysis: Estimation
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MLR: Estimation
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Motivation for Multiple Regression
Motivation for Multiple Regression
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MLR: Estimation
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Mo

Multiple Regression Analysis: Estimation
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The University of Hong Kong
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MLR: Estimation
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Motivation for Multiple Regression
Motivation for Multiple Regression
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Mo

Multiple Regression Analysis: Further Issues
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Effects of Data Scaling on OLS Statistics
Effects of Data Scaling on OLS Statistics
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MLR