ECON704 Discussion 3: Answer Key
Wooyoung Kim
Sep 26, 2014
1. (a) 0 + 201 + 2
(b) The expected test score of Maya would increase by |151 |, all else
unchanged.
2. (a) (see Lecture Note 3, p.10) The error term can be understood as
summarizing the factors t
Large-Sample Approximations
Wooyoung Kim
University of Wisconsin-Madison
October 16, 2014
Wooyoung Kim
Large-Sample Approximations
Introduction
Lets begin with a benchmark case as below:
Suppose you are risk-neutral.
You ip the coin: you can get nothing w
ECON704 Discussion 3
Wooyoung Kim
Sep 26, 2014
1
Problem Set 1 Review
a
, where a is a
scalar, is a k 1 vector and is a k k matrix. Find the element
at the rst row and rst column of A1 . You can assume invertibility of
anything that needs to be inverte
ECON704 Discussion 6 Answer Key
Wooyoung Kim
Oct 17, 2014
1
Exercises
1. (From Lecture Note 5 Ex.1(d) Let Xi = (1, Xi ) for all i. Write down
n
1
E[n
i=1 Xi Yi ] in terms of Xi and Yi .
Answer:
n
n
1
Xi
Xi Yi ] = E[n1
E[n1
i=1
i=1
n
= n1
= n1
i=1
= n1
Yi
ECON704 Discussion 2
Wooyoung Kim
Sep 19, 2014
Before start: Linear algebra and probability are not the focus of this class.
DONT spend too much time to understand every small feature about them.
Instead, use it as a reference when we advance to econometr
Final Exam (12/18/2013, 5:05pm - 7:05pm)
1. Please do not turn this page over until you are instructed otherwise.
2. Try to follow the suggested time for each question. Each minute corresponds
to one point. There are 100 points in total. If you nish in su
ECON704 Discussion 1
Wooyoung Kim
Sep 12, 2014
1
General Information
My name is Wooyoung Kim(wkim68@wisc.edu), 2nd year Ph.D. student
in economics.
Oce Hours : Monday 1-2PM, Thursday 10:30-11:30AM @ SS7218
Please send your questions before visiting my
ECON704 Discussion 9
Wooyoung Kim
Nov 7, 2014
1
Midterm II Notication
Date: Nov 12 (next Wednesday) in class (no extra time)
Location: EDU L196 (Same as Midterm I)
TA Oce hours: Mon 1-2pm, Tue 10:30-11:30am, 4-5pm (No oce hour on Thursday)
2
How to per
ECON704 Discussion 13
Wooyoung Kim
Dec 12, 2014
1
Final Information
Hours: Dec 18 (Next Thursday) 5:05-7:05 PM (There will be some extra time if you want)
Location: 5106 Social Science
Checking Grade / Claim : Hopefully Dec 20 (Saturday) morning but no
1
Exercises
1. Review Example 3 in Lecture 4. Suppose that you want to estimate the production function of an industry of a certain product (say, cement). Assume that
the production function is of the Cobb-Douglas form described in the question.
Also supp
ECON704 Discussion 12
Wooyoung Kim
Dec 5, 2014
1
STATA: ivregress
How can we apply instrument variable approach in STATA? You can use the
command ivregress.
Use CARD.DTA. We want to estimate the following causal model:
log(W age) = 0 + 1 Educ + 2 Exper +
Reading Instruction:
Focus on Introduction, Section I and III.
American Economic Association
American Economic Association
http:/www.jstor.org/stable/30034396 .
Your use of the JSTOR archive indicates your acceptance of the Terms & Conditions of Use, avai
Econ 704: Econometrics I
Instructor: Xiaoxia Shi
TA: Wooyoung Kim
Lectures: MW 2:30pm-3:45pm SS 5231.
TA sessions: TBA
Instructor Office Hours: MW 3:45pm 4:45pm.
TA Office Hours: M 1:00pm-2:00pm, Th 10:30am 11:30am.
Course webpage: We will be using Piazza
Quiz 4 12/01
Let Y be a dependent variable, X1 and X2 be two treatment variables. Let the
causal model for Y be:
Y = 0 + 1 X1 + 2 X2 + U,
(1)
where U summarizes other factors that contributes to the generation of Y . Assume
that E(U |X1 , X2 ) = E(U ). Un
Problem Set 5, due 12/03, before class starts.
1. Exercise Questions 1 in Lecture 9
(a) Answer: The paper studies the causality between a fully anticipated temporary wage increase and 1) working time choice and 2) the eort during
working time.
(b) Answer:
Problem Set 4, due 11/10, before class starts.
1. Let Y be a dependent variable and X = (1, D) , where D is an indicator
variable. Consider the estimation of the model E(Y |X) = 0 + 1 D using an
i.i.d. sample cfw_(Yi , Di )n of (Y, D). Let (0 , 1 ) .
i=1
Problem Set 6, due 12/16 1pm in Wooyoungs mailbox
1. Exercise Questions 1 in Lecture 10
Table 1: Estimation
(a)
coef.(s.e.)
cigs
-0.222
(-1.538)
cig0
5.881*
(2.430)
parity
fatheduc
white
male
constant
114.180*
(48.660)
results
d (b)
coef.(s.e.)
-0.425*
(-
Problem Set 4, due 11/10, before class starts.
1. Let Y be a dependent variable and X = (1, D) , where D is an indicator
variable. Consider the estimation of the model E(Y |X) = 0 + 1 D using an
i.i.d. sample cfw_(Yi , Di )n of (Y, D). Let (0 , 1 ) .
i=1
Problem Set 5, due 12/03, before class starts.
1. Exercise Questions 1 in Lecture 9
2. Exercise Questions 3 in Lecture 9
3. Exercise Questions 4 in Lecture 9
4. Exercise Questions 5 in Lecture 9
5. Exercise Questions 6 in Lecture 9
6. Exercise Questions 9
Problem Set 3 Solution, due 10/29, before class starts
1. Suppose that you have two independent unbiased estimators 1 and 2 of the
same parameter . Suppose that V ar(1 ) = v1 and V ar(2 ) = v2 . What linear
combination (c) = c1 1 +c2 2 makes the minimum v
Problem Set 2, due 10/08
1. This question helps you to understand the three dierent interpretations and
their underlying assumptions for a regression equation.
Suppose that the random variables of interest are: X:undergraduate GPA, and
Y :salary of the rs
Problem Set 3, due 10/27, before class starts
1. Suppose that you have two independent unbiased estimators 1 and 2 of the
same parameter . Suppose that V ar(1 ) = v1 and V ar(2 ) = v2 . What linear
combination (c) = c1 1 +c2 2 makes the minimum variance u
Problem Set 2, due 10/06, before class starts, total 4 pages
1. This question helps you to understand the three dierent interpretations and
their underlying assumptions for a regression equation.
Suppose that the random variables of interest are: X:underg
Problem Set 1 with answer
a1
a2
1. Let A := . be a n k matrix.
.
.
an
(a) Show that A A =
n
i=1
ai ai .
Answer:
n
n
ai ai =
i=1
i=1
a2
ai1 ai2 ai1 aik
i1
ai1 ai2 a2
ai2 aik
i2
.
.
.
.
.
.
.
.
.
.
.
ai1 aik ai2 aik
a2
ik
And,
an1
a11 a12
Problem Set 1, due 9/22 before class starts
a1
a2
1. Let A := . be a n k matrix.
.
.
an
(a) Show that A A =
n
i=1
ai ai .
(b) Show that AA = (ai aj )n n .
i=1 j=1
(Please do the proof in this question using the basic denition of matrix product
giv
Midterm Exam 2 (11/13/2013, 1:00pm - 2:15pm)
1. Please do not turn this page over until you are instructed otherwise.
2. Try to follow the suggested time for each question. Each minute corresponds
to one point. There are 60 points in total. If you nish in