EC355 Fall 2014
1)
Practice Final Exam Questions
Consider the following population regression model relating the dependent variable Yi
and regressor Xi,
Yi = 0 + 1Xi + ui, i = 1, n.
X i Yi + Zi
where Z is a valid instrument for X.
(a)
Explain why you shou
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Fifteen
Instrumental Variables Estimation
and Two Stage Least Squares
I
n this chapter, we further study the problem of endogenous explanatory variables
in multiple regression models. In Chapter 3, we derived the b
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B
Fundamentals of Probability
T
his appendix covers key concepts from basic probability. Appendices B and C
are primarily for review; they are not intended to replace a course in probability
and statistics. Neve
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Six
Multiple Regression Analysis:
Further Issues
T
his chapter brings together several issues in multiple regression analysis that we
could not conveniently cover in earlier chapters. These topics are not as fundam
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Four
Multiple Regression Analysis:
Inference
T
his chapter continues our treatment of multiple regression analysis. We now turn
to the problem of testing hypotheses about the parameters in the population
regression
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Fourteen
Advanced Panel Data Methods
I
n this chapter, we cover two methods for estimating unobserved effects panel data
models that are at least as common as first differencing. Although these methods are
somewhat harder to describe and imp
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Seven
Multiple Regression Analysis with
Qualitative Information: Binary
(or Dummy) Variables
I
n previous chapters, the dependent and independent variables in our multiple regression models have had quantitative me
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Ten
Basic Regression Analysis with
Time Series Data
I
n this chapter, we begin to study the properties of OLS for estimating linear regression
models using time series data. In Section 10.1, we discuss some conceptual differences between tim
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Thirteen
Pooling Cross Sections Across
Time. Simple Panel Data
Methods
U
p until now, we have covered multiple regression analysis using pure crosssectional or pure time series data. While these two cases arise oft
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Angrist, J. D. (1990), Lifetime Earnings and the Vietnam
Era Draft Lottery: Evidence from Social Security
Administrative Records, American Economic Review
80, 313336.
Angrist, J. D., and A. B. Krueger (1991), Does
Com
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Title: Economic Impact of International Education in Canada
Year: 2011
Location: http:/www.international.gc.ca/education/report-rapport/economic-impacteconomique/sec_5.aspx?lang=eng#living_expenses_52
Major spending for long term students:
1.Secondary
2.T
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Adjusted R-Squared: A goodness-of-fit measure in
multiple regression analysis that penalizes additional
explanatory variables by using a degrees of freedom
adjustment in estimating the error variance.
Alternative
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Nineteen
Carrying out an Empirical Project
I
n this chapter, we discuss the ingredients of a successful empirical analysis, with
emphasis on completing a term project. In addition to reminding you of the important
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D
Summary of Matrix Algebra
T
his appendix summarizes the matrix algebra concepts, including the algebra of
probability, needed for the study of multiple linear regression models using
matrices in Appendix E. No
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E
The Linear Regression Model in
Matrix Form
T
his appendix derives various results for ordinary least squares estimation of the
multiple linear regression model using matrix notation and matrix algebra (see
App
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Answers to Chapter Questions
CHAPTER 2
QUESTION 2.1
When student ability, motivation, age, and other factors in u are not related to attendance, (2.6) would hold. This seems unlikely to be the case.
QUESTION 2
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Fundamentals of Mathematical
Statistics
C.1 POPULATIONS, PARAMETERS, AND
RANDOM SAMPLING
Statistical inference involves learning something about a population given the availability of a sample from that popula
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G
Statistical Tables
TABLE G.1
Cumulative Areas Under the Standard Normal Distribution
z
0
1
2
3
4
5
6
7
8
9
3.0
2.9
2.8
2.7
2.6
2.5
2.4
2.3
2.2
2.1
2.0
1.9
1.8
1.7
1.6
1.5
1.4
1.3
1.2
1.1
1.0
0.9
0.8
0.7
0.0013
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One
The Nature of Econometrics and
Economic Data
C
hapter 1 discusses the scope of econometrics and raises general issues that result
from the application of econometric methods. Section 1.3 examines the kinds of
dat
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T wo
The Simple Regression Model
T
he simple regression model can be used to study the relationship between two
variables. For reasons we will see, the simple regression model has limitations as a general tool for e
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Three
Multiple Regression Analysis:
Estimation
I
n Chapter 2, we learned how to use simple regression analysis to explain a dependent variable, y, as a function of a single independent variable, x. The primary drawb
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Five
Multiple Regression Analysis:
OLS Asymptotics
I
n Chapters 3 and 4, we covered what are called finite sample, small sample, or exact
properties of the OLS estimators in the population model
y
0
x
11
x
22
x
kk
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Eight
Heteroskedasticity
T
he homoskedasticity assumption, introduced in Chapter 3 for multiple regression, states that the variance of the unobservable error, u, conditional on the
explanatory variables, is consta