ECON 4000
TEST #2 ANSWER KEY
SPRING 2011
Instructions: All questions must be answered on this examination paper; no extraneous
sheets of paper will be graded. Point values for each question are in par
ECON 4000
TEST #1
ANSWER KEY
SPRING 2011
Instructions: All questions must be answered on this examination paper; no extraneous
sheets of paper will be graded. Point values for each question are in par
TIME-SERIES REGRESSION
1
Implications for OLS
Basic time-series regression model:
yt = 0 + 1 xt1 + + K xtK + ut ,
t = 1, . . . , T
(1)
How do you distinguish the population from the sample in a time-s
2
Trending Series
2.1 Deterministic Trends
Including a trend among the regressors does not violate any ts assumptions;
omitting a trend when present in the underlying process can result in a
spurious
5
Proxy Variables and Measurement Error
5.1 Proxy Variables
5.1.1 Conditions for Unbiasedness and Consistency
Consider
y = 0 + 1 x1 + 2 x2 + 3 x3 + u,
where x3 is unobserved and primary interest is in
7
Panel Data
7.1 Repeated Cross-sections vs Panels
In cross-section data, we assume the random variables that comprise the
regression model are iid draws from some population.
In repeated cross-sectio
6
Instrumental Variables
6.1 Motivation
IV motivated by violations of MLR.4, which implies
E(xik ui ) = 0,
k = 1, . . . , K
A variable that does not satisfy the uncorrelatedness conditions implied by
# Reading the data
# make sure to check if there is a heading or not, if so add ,h=T
data1= read.table("data2.1.txt")
# creating a regression from data
g=lm(sr~pop15+pop75+dpi+ddpi,data=savings)
# giv
STAT 4220
R Introduction and Preliminaries
1.1
The R Environment and Language
R is an integrated suite of software facilities for data manipulation, calculation and
graphical display.
The benefits of
3
Autocorrelation
3.1 Consequences for OLS
Consider the GM assumptions for time-series models.
What are the consequences for OLS if TS.5 does not hold?
Is OLS still BLUE? Consistent? Does a CLT still
CROSS-SECTION REGRESSION
1
Simple Regression
1.1 Introduction
Simple regression model:
E(yi | xi ) = 0 + 1 xi ,
where yi is the dependent variable or regressand and xi is the explanatory
variable or r
ECON 4000
ECONOMICS OF HUMAN RESOURCES
Professor Warren
Course Syllabus: Spring 2011
The syllabus is a general plan for the course; deviations
announced to the class by the instructor may be necessary
ECON 4000
TEAM PROJECT
SPRING 2011
Deliverables:
Resume: You must submit a resume to me by the beginning of class on Wednesday, January 26th. In
completing your resume, you should carefully adhere to
ECON 4000
TEST #1
SPRING 2011
Instructions: All questions must be answered on this examination paper; no extraneous
sheets of paper will be graded. Point values for each question are in parentheses to
ECON 4000
TEST #2
SPRING 2011
Instructions: All questions must be answered on this examination paper; no extraneous
sheets of paper will be graded. Point values for each question are in parentheses to
FALL 16
ECONOMICS 4750
PROBLEM SET 2
Solutions
CORNWELL
Part A
1.1. (8 points) Some obvious factors are income, age and number of siblings. Each of these could be
correlated with education: income, po
Fall 2016
Economics 4750
Problem set 1
Solutions
Cornwell
Appendix B
B.1 (5 points)
Before the student takes the SAT exam, we do not know nor can we predict with certainty
what the score will be? The
FALL 15
ECONOMICS 4750
PROBLEM SET 4
Solutions
CORNWELL
Part A
Chapter 3
9.1. (6 points) House prices should fall with pollution (1 < 0) and rise with the number of rooms
(2 > 0).
9.2. (6 points) If r
4
Heteroscedasticity
4.1 Consequences for OLS
Recall MLR.5:
var(ui | xi1 , . . . , xiK ) = 2 ,
which says that 2 does not depend on the regressors.
OLS is unbiased and consistent, even if (MLR.5) is v
ECON 4000
DETAILED COURSE OBJECTIVES
SPRING 2011
After completing this course, you will be able to:
1. Explain the costs and benefits that should be considered in deciding how many workers to hire and