ECON 531  Econometrics  Spring 2017
Homework Assignment 2 Answer Key
1
1.
Consider the estimated equation that studies the effects of skipping class on college GP A:
= 1.39 + .412 + .015 .083
(.33)
(.094)
(.011)
(.026)
n = 141, R = .234.
2
(i)
Using t
ECON 301 Econometrics Fall, 2013
Midterm Exam I
Answer Key
1. (25 points) Consider two random variables X and Y which have the following joint probability distribution:
0
1
2
0
1/3
0
0
1
1/6
1/3
1/6
Y
a)
b)
c)
d)
X
Are X
Review Questions: Final Exam
Review Questions: Exam 1
Review Questions: Exam 2
Review Questions for New Material
1. Suppose you have information on male and female workers in a company, and you wish to estimate the
effects of workplace experience
ECON 531  Econometrics  Spring 2017
Homework Assignment 2
1
1.
Consider the estimated equation that studies the effects of skipping class on college GP A:
= 1.39 + .412 + .015 .083
(.33)
(.094)
(.011)
(.026)
n = 141, R = .234.
2
2.
(i)
Using the st
ECON 531  Econometrics  Fall 2017
Homework Assignment 1 Due on October 29
1
1.
Let X be a random variable distributed as Normal (5,4). Find the probabilities of the following events:
(i) P(X 6).
(ii) P(X> 4).
(iii) P(2<X<4).
2.
Let X and Y be
Econometrics (ECON 531)
Outline of Lecture Notes for Chapter 1
(Based on Introductory Econometrics by Jeffery M. Wooldridge)
Chapter 1: The Nature of Econometrics and Economic Data
I. What is Econometrics?
II. Steps in Empirical Economic Analysis
Step 1:
ECON 531  Econometrics  Spring 2017
Homework Assignment 3
1.
Suppose you collect data from a survey on wages, education, experience, and gender. In addition, you ask for
information on marijuana usage. The original question is: On how many separate occa
Review Questions for Exam 1
1. Consider a continuous random variable X with E(X) = 4 and Var(X) = 6. Suppose we draw a
random sample of ten xs and label them 1 , 2 , . , 10 . What is the mean and variance of the
sample average ?
2. Suppose you are interes
Econ 531: Econometrics
Spring 2017
Review Questions: Exam 2
1. The OLS fitted line explaining college GPA in terms of high school GPA and ACT score is
= 1.29 + 0.453 + 0.0094 .
If the average high school GPA is about 3.4 and average ACT score is about 24
SUMMARY OF SIMPLE LINEAR REGRESSION
Assumptions
SLR.1 Linear in Parameters:
I Population model follows )2 = [80 + lx + u
SLR.2 Random Sampling
' There is a random sample of size n
' cfw_(xiayi); i=l,.,n
SLR.3 Sample Variation
I The sample outcomes cfw_x5
VI.
Units of Measurement and Functional Form
A. Using the Natural Logarithm in SRM
1) Constant Marginal Return to Education
2) Constant Percentage Effect (SemiElasticity Model)
2
3) Constant Elasticity Model
3
B. Units of Measurement
= ! + ! +

Econometrics (ECON 531)
Outline of Lecture Notes for Chapter 2
(Based on Introductory Econometrics by Jeffery M. Wooldridge)
Chapter 2: The Simple Regression Model (SRM)
I. Definition of the Simple Regression Model
A) Simple linear regression model
B) Ass
Econometrics (ECON 531)
Outline of Lecture Notes for Chapter 4
(Based on Introductory Econometrics by Jeffery M. Wooldridge)
Chapter 4: Multiple Regression Analysis: Inference
I. Review
A) The normal and related distributions (Appendix B.5)
1) Normal dist
Econometrics (ECON 531)
Outline of Lecture Notes for Chapter 3
(Based on Introductory Econometrics by Jeffery M. Wooldridge)
Chapter 3: Multiple Regression Analysis
I. Motivation for Multiple Regression
Examples
Notation
Interpretation of coefficients
Econometrics (ECON 531)
Outline of Lecture Notes for Chapter 5
(Based on Introductory Econometrics by Jeffery M. Wooldridge)
Chapter 5: Multiple Regression Analysis: OLS Asymptotics
I. Review  Asymptotic or Large Sample Properties of Estimators (Appendix
Econometrics (ECON 531)
Outline of Lecture Notes for Appendix B (B.1B.4)
(Based on Introductory Econometrics by Jeffery M. Wooldridge)
Review of probability (Appendix B.1 B.4)
I. Random Variables and Their Probability Distribution
A) Experiment
B) Random
ECON 531  Econometrics  Spring 2017
Homework Assignment 1 Answer Key
1
1.
Let X be a random variable distributed as Normal (5,4). Find the probabilities of the following events:
(i) P(X 6).
(ii) P(X> 4).
(iii) P(2<X<4).
Answer:
~ (5,4)
5
=
2
E(Z) = 0;
ECON 301: ECONOMETRICS I
Assignment 8
Due: Tuesday, November 22 at 6 pm
Instructions:
1) You can work in groups, but you need to submit your own original answers. Copying or
paraphrasing (even part of) someone elses answers is NOT working together. Acade
ECON 301: ECONOMETRICS I
Assignment 3
Due: Sunday, September 18 at 6 pm
Instructions:
1) You can work in groups, but you need to submit your own original answers. Copying or
paraphrasing (part or all of) someone elses answers is NOT working together. Aca
ECON 301: ECONOMETRICS I
Assignment 4
Due: Tuesday, September 27 at 11:59 pm
Instructions:
1) You can work in groups, but you need to submit your own original answers. Copying or
paraphrasing (even part of) someone elses answers is NOT working together.
September 27, 2016
ECON 301: ECONOMETRICS I
Assignment 4 Answer Key
Part I: EndofChapter 4 Questions
1. i) and (iii) generally cause the t statistics not to have a t distribution under H0.
Homoskedasticity is one of the CLM assumptions. An important omi
September 18, 2016
ECON 301: ECONOMETRICS I
Assignment 2 Answer Key
Part I: EndofChapter 2 Questions
2. In the equation y= 0 + 1 x +u , add and subtract 0 from the right hand side to get
y= 0 + 0 + 1 x+ u 0 . Call the new error e=u 0 , so that E(e) = 0.
ECON 301: ECONOMETRICS I
Assignment 2
Due: Friday, September 9 at 6 pm
Instructions:
1) You can work in groups, but you need to submit your own original answers. Copying or
paraphrasing (part or all of) someone elses answers is NOT working together. Acad
28 September 2016
ECON 301: ECONOMETRICS I MIDTERM ANSWER KEY
Time allowed: 90 minutes
IMPORTANT: Explain your answers carefully. You get no credit for unsupported assertions or
guesses. Write as if you are trying to convince an intelligent person who doe
September 9, 2016
ECON 301: ECONOMETRICS I
Assignment 2 Answer Key
Part I: EndofChapter 1 Questions
1. (i) Ideally, we could randomly assign students to classes of different sizes. That is, each
student is assigned a different class size without regard