Econometrics Spring 2013
Lecture Note 4: Linear Regression with One Regressor
(SW 4.14.5)
1
The Linear Regression Model and Assumptions
The model we consider is
Yi = 0 + 1 Xi + ui
for i = 1, . . . , n, where
Yi is the dependent variable, the regressand,
University of California, San Diego
Economics 120B
Summer Session II 2015
Problem Set 1
Due Wednesday, Aug. 19
Please staple your Stata output (.log) file to your answers. Include the Stata output
for results you report in question #4.
1. Sir Francis Galt
ECON 120C  SYLLABUS (SUMMER II, 2015)
Foster, UCSD, September 4, 2015
Teaching Staff and Consultation Hours
Name/Position
Times
Room
Contact Info
MW
Carroll B. Foster
ECON
11cfoster @ mail.ucsd.edu
(PhD/Lecturer)
110C
noon
Roy Allen
rhallen @ ucsd.edu
Ka
Problem Set 3, Econ 120B
Prof. Yixiao Sun
Due on August 28
Part A
1. Let
Y = E (Y jX) + [Y
where f (X) = E (Y jX) and u = Y
E (Y jX)] = f (X) + u
E (Y jX) : Show that Eu = 0:
2. Let Y = X 3 +u where X and u are independent standard normals. Compute E (Y j

name: <unnamed>
log: C:\Users\shlay\Desktop\Sharon Lay HW 3.log
log type: text
opened on: 11 Mar 2015, 17:10:55
. gen ln_income=ln(income)
. reg fatalityrate sb_useage speed65 speed70 ba08 drinkage21 ln_income age, r
Linear regression Number of obs
Economics ALL COURSES
Foster, UCSD
EXCEL INSTRUCTIONS
February 8, 2017
PART I  BASICS (IN, OUT, & WORKBOOKS)
Notation
Convention
boldface
SMALL CAPITALS
Italics
,
,
<CtrlShftEnter>
Meaning
What you enter (type) from keyboard
Window, program and icon n
Ec 120C ECONOMETRICS C
Foster, UCSD, due Monday of 2nd week
HW #1 MULTIPLE OLS REGRESSION
The Problem
You have the following regression model: REC = 1 + 2 FAM + 3 INC + 4 EDU + 5 VAC, where:
REC = family recreational expenditure ($1000/yr)
FAM = family
Ec 120C ECONOMETRICS C
Foster, UCSD, due 4th Tuesday, in class
HW #3  COMPLICATIONS
Preliminaries
Data on state and local government expenditures are in Table A. For states i = 150 and year 1970:
ge = per capita state and local govt expenditure
s, e, n
Ec 120C ECONOMETRICS
Foster, UCSD, due Monday of 3rd week
HW #2  APPLICATIONS
Some notation:
= leftclick; = doubleclick; = rightclick
bold = what you type in STATA
italic = my comments on commands and results
This That = sequential choices in drop
University of California, San Diego
Department of Economics
Summer Session II 2015
ECON 120B: Econometrics
Prof. Augusto Nieto Barthaburu
Lectures: TuTh 11:001:50 PM at Center Hall 113
Discussion section: W 2:003:50 PM (location TBA)
Email: [email protected]
Econ 120B: Econometrics
Summer Session II, 2015
UCSD
Confidence Intervals
Confidence Intervals
A 95% confidence interval for Y is an interval that contains the
true value of Y in 95% of repeated samples.
Digression: What is random here? The values of Y1,Y
Econ 120B: Econometrics
Summer Session II, 2015
UCSD
Regression with a Single Regressor:
Hypothesis Tests and Confidence Intervals
Overview
Now that we have the sampling distribution of OLS
estimator, we are ready to perform hypothesis tests about 1
and
Econ 120B: Econometrics
Summer Session II, 2015
UCSD
Probability: events best thought of as uncertain
Events:
A Chargers beat Raiders on Sunday (0no,1yes)
B  Chargers beat Raiders by over ten points
C  Alibaba stock price rises above $90 sometime this
Econ 120B: Econometrics
Summer Session II, 2015
UCSD
Discussion Section Tomorrow
Tomorrows section will be held in the computer
lab at SH 142 once again
The TA will show you how to import data and
compute sample statistics and regression using
Stata
12
Econ 120B: Econometrics
Summer Session II, 2015
UCSD
Heteroskedasticity and Homoskedasticity
What do these two terms mean?
o If var(uX=x) is constant that is, if the variance of the
conditional distribution of u given X does not depend on X
then u is s
Ec 120BC ECONOMETRICS B and C
Foster, UCSD
LECTURE NOTES
September 4, 2015
TOPIC 12. MULTIPLE OLS REGRESSION
A. Classical Multiple Linear Regression Model
1. Assumptions of the OLS Model:
A
1
A
2
A
3
A
4
A
5
A
6
CLRM Assumptions
Yi = 1 + 2Xi + 3Wi + + kHi
Ec 120B  ECONOMETRICS B
Foster, UCSD
LECTURE NOTES
September 4, 2015
TOPIC 11. SIMPLE OLS REGRESSION
A. Overview of Econometrics
1. Definitions:
a) Econometrics the application of mathematical/statistical methods to economic data to
investigate relations
Ec 120C ECONOMETRICS C
Foster, UCSD, due 5th Monday, in class
HW #4 SERIAL CORRELATION & LAGGED VARIABLES
The Problem
Preliminaries
You have annual data on variables Y, M, L and G for the period 19732013 (t = 141).
Y = GDP
M = money supply
L = labor forc
The Islamic University of Gaza
Faculty of Commerce
Economics Department
Econometrics & Quantitative Analysis Dr. Samir Safi
2/3/2013
Midterm Examination #1
NAME:_ID:_
Question #1 (20 Points):
For each question below, circle the correct answer
1) Analyzing
Chapter 4 & 5
CHAPTER 4  Agency:
1. Who is considered the Principal in a real estate relationship? Define
'agency' as according to the California Civil Code. Explain what is a Fiduciary
Relationship, how is it created and how does it obligate the agent?
Introduction
to Econometrics
James H . Stock
HARVARD UNIVERSITY
Mark W . Watson
PRINCETON UNIVERSITY
Boston San Francisco N e w York
London Toronto Sydney Tokyo Singapore Madrid
Mexico City Munich Paris Cape Town Hong Kong Montreal
Brief Contents
PART O N
Econometrics Spring 2013
Lecture Note 2: Review of Probability (2.52.6)
1
Random Sampling and the Distribution of the Sample Average
1.1
Random sampling
In statistical inference, it is important to distinguish the dierence between population and sample.
Econometrics Spring 2013
Lecture Note 5: Regression with a Single Regressor: Hypothesis
Tests and Condence Intervals (SW 5.15.4)
1
Testing Hypotheses About One of the Regression Coecients
1.1
TwoSided Hypotheses Concerning 1
Testing hypotheses about the
Econometrics Spring 2013
Lecture Note 1: Review of Probability (SW 2.12.4)
1
Sample Space and Probability
Denition 1 (Experiment)
An experiment is a process with an observable uncertain outcome.
Denition 2 (Sample space)
The sample space () is the set of
Econometrics Spring 2013
Lecture Note 7: Hypothesis Tests and Condence Intervals in
Multiple Regression (SW 7.17.3, 7.5)
1
Hypothesis Tests and Condence Intervals for a Single Coecient
1.1
Hypothesis Tests for a Single Coecient
The model is
Yi
= 0 + 1 X1
Econometrics Spring 2013
Lecture Note 3: Review of Statistics (SW 3.13.3)
1
Estimation of the Population Mean
Suppose that you want to know the population mean. Given i.i.d. observations Y1 , . . . , Yn with E[Yi ] =
and Var[Yi ] = 2 , the most natural
Midterm, Econ120B
Summer 2013, UCSD, Professor: Yixiao Sun
Last Name
First Name
UCSD PID
INSTRUCTIONS
1. Do not turn this page until instructed.
2. The exam has a total of 100 points. The number of points for each question is indicated with
the question.
Problem Set 3, Econ 120B
Prof. Yixiao Sun
Due on August 28
Part A
1. (1) Let
Y = E(Y jX) + [Y
where f (X) = E(Y jX) and u = Y
E(Y jX)] = f (X) + u
(1)
E(Y jX): Show that Eu = 0:
<Answer> It is straight forward to show that Eu = E [Y E(Y jX)] = E[Y ] E [E(