Name:
By writing my name I. swear not to give or receive aid on this exam
Midterm Exam.
You~ may only use a nomprogrammable calculator, though you probably do not need one.
Cell phones may not be used for any reason. Please explain your answers brie
Homework 6
EC 320
Professor Piger
Fall 2014
Due: Wednesday, November 19
Analytical Exercises
1) Consider the following multiple linear regression model:
Yi = 1 + 2 X 2i + 3 X 3i + 4 X 4i + 5 X 5i + ui
(Equation 1)
You want to test the null hypothesis that
Introduction to Regression Analysis
EC 320
Professor Jeremy Piger
1/35
Introduction to Regression Analysis
Readings: Dougherty Chapter 1
Regression Analysis
Simple Linear Regression Model
Estimating the Parameters of the Linear Regression Model
Ordina
EC 320
Solutions to Midterm Practice Problems
Solution to Practice Problem 1:
Expected Value = 8*0.75 + -4*0.25 = 5
2
Variance = (8 5) * 0.75 + (4 5) 2 * 0.25 = 9 * 0.75 + 81 * 0.25 = 27
Solution to Practice Problem 2:
There are 16 different equally likel
Homework 6
EC 320
Professor Mastromonaco
Winter 2014
Due: Thursday, February 27th
Analytical Exercises
1) (6 points) Consider the following multiple linear regression model:
Yi = 1 + 2 X 2i + 3 X 3i + 4 X 4i + 5 X 5i + ui
(Equation 1)
You want to test the
Midterm Solutions (GREEN)
EC 320
Professor Mastromonaco
Spring 2016
NAME:_
Instructions:
1. Answer all questions below.
2. Write your answers in the space provided.
3. Statistical tables are included at the end of the exam.
4. There are 100 points possibl
EC 320 Midterm Practice Problems
Practice Problem 1: Consider a discrete random variable that takes a value of 8 with
probability 0.75 and a value of -4 with probability 0.25. Calculate the expected value of
this random variable and its variance.
Practice
Homework 2
EC 320
Professor Piger
Fall 2014
Due: Wednesday, October 15 (in class)
Analytical Exercises
1) Consider a sample of size n = 3 on a dependent variable Y and an independent
variable X:
Observation Number
Value of Y
Value of X
1
4
-4
2
4
2
3
7
2
UNIVERSITY OF OREGON
Department of Economics
Introduction to Econometrics
Fall 2014
EC 320, CRN 12030
MW 12:00 a.m. 1:20 a.m. in McKenzie 240A
Instructor: Jeremy Piger
Contact Information: Office: 536 PLC; Email: [email protected]; Phone: 541-346-6075
Of
Homework 5
EC 320
Professor Piger
Fall 2014
Due: Wednesday, November 12
Analytical Exercises
1) Data was collected from a random sample of 220 home sales from a community in
2003. Let P denote the selling price (in $1000), Bdr denote the number of bedroom
Homework 7
EC 320
Professor Piger
Fall 2014
Due: Wednesday, November 26
Note: Homework assignments may be turned in during class on Monday, November 24, or
to Professor Pigers oce at any time up until noon on November 26.
Analytical Exercises
1) Youve bee
Econ 320
Dr. Ralph Mastromonaco
University of Oregon
Spring 2015
SYLLABUS: Introduction to Econometrics
Time M-W 10:00 am 11:20 am
Location 145 Straub
Professor
Ralph Mastromonaco
533 PLC
[email protected]
Office Hours
Monday & Wednesday 12 1 pm
Course D
Introduction to:
Econometrics: EC 320
Dr. Ralph Mastromonaco
University of Oregon
Introduction to: Econometrics: EC 320
University of Oregon
Syllabus
Please Read The Syllabus!
Introduction to: Econometrics: EC 320
University of Oregon
A Philosophical Appe
Random Variables
Expected Value
Variance, Covariance, Correlation
Estimation
Properties of Estimators
Review of Statistics
Dr. Ralph Mastromonaco
University of Oregon
Review of Statistics
University of Oregon
Random Variables
Expected Value
Variance, Cova
Hypothesis Testing
Doing a Test
Generalizing the test
Error and Power
Hypothesis Testing in OLS
Hypothesis Testing
Dr. Ralph Mastromonaco
University of Oregon
Hypothesis Testing
University of Oregon
Hypothesis Testing
Doing a Test
Generalizing the test
Er
Multiple Regression Analysis
Interpretation
Estimation
Frisch-Waugh
Properties
Multiple Linear Regression
Dr. Ralph Mastromonaco
University of Oregon
Multiple Linear Regression
University of Oregon
Multiple Regression Analysis
Interpretation
Estimation
Fr
Regression Analysis
Simple LRM
Estimation
OLS
Introduction to Regression Analysis
Dr. Ralph Mastromonaco
University of Oregon
Introduction to Regression Analysis
University of Oregon
Regression Analysis
Simple LRM
Estimation
OLS
Introduction to Regression
Introduction
NL in Variables
NL in Parameters
Comparing Linear and Log
Non-linearity
Dr. Ralph Mastromonaco
University of Oregon
Non-linearity
University of Oregon
Introduction
NL in Variables
NL in Parameters
Comparing Linear and Log
Functional Forms and
Classical Assumptions
Random vs. Non Random
Bias and Precision
PDF
Monte Carlo
Statistical Properties of the OLS Estimator
Dr. Ralph Mastromonaco
University of Oregon
Statistical Properties of the OLS Estimator
University of Oregon
Classical Assumptions
R
OLS Review
Regression Analysis
Beauty
Earnings and Height
Introduction to Regression Analysis
Dr. Ralph Mastromonaco
University of Oregon
Introduction to Regression Analysis
University of Oregon
OLS Review
Regression Analysis
Beauty
Earnings and Height
Si
RVs
Regression & Testing
Econometrics:
Midterm Review
Dr. Ralph Mastromonaco
University of Oregon
Econometrics: Midterm Review
University of Oregon
RVs
Regression & Testing
Review of Class
Readings: Dougherty
Chapter R
Chapter 1
Chapter 2
Econometrics: Mi
Dummy Variables
Dr. Ralph Mastromonaco
University of Oregon
Dummy Variables
University of Oregon
Dummy Variables
Readings: Dougherty Chapter 5
Quantitative vs. Qualitative Information
Uses of Dummy Variables
Dummy Variables with Multiple Categories
The Du
Nicole Korkos
HW #4
EC 320
Written Work
1. Fail to reject at the 1% level, but reject it at the 5% level. This is because at the 1% level the
p-value to reject the null must be less than .01, at the 5% level the p-value you need to reject the
null must be
Quiz 2
EC 320
Professor Piger
Spring 2017
NAME:_
Instructions:
1. Answer all questions below.
2. Write your answers in the space provided.
3. You have 40 minutes to complete the quiz.
4. You must show your work to receive credit.
5. There are 25 points po
EC 320 Final Exam Practice Problems
Note: These practice problems are taken from material covered since the midterm. For
practice problems covering material presented before the midterm, see the first quiz,
midterm, midterm practice problems, and homework
Homework 1
EC 320
Professor Piger
Fall 2014
Due: Wednesday, October 8 (in class)
Read This First: Homework in this course will include both analytical and computer
exercises. The computer exercises will involve extensive work with statistical software
pac
Homework 8
EC 320
Professor Piger
Fall 2014
Due: Friday, December 5
Analytical Exercises
1) Stock market investors give considerable attention to a firms quarterly earnings
announcement, in which the firm releases its quarterly accounting earnings.
Suppos