Professor Mumford
mumford@purdue.edu
Econ 360 - Fall 2012
Problem Set 4
Due at the beginning of class on Tuesday, September 18
True/False
(10 points) Please write the entire word. No explanations are required.
1. Heteroskedasticity causes the OLS estimato
ECON 360 Problem Set 4 Solutions
WOOLDRIDGE CHAPTER 2
2.7
(i) When we condition on inc in computing an expectation, becomes a constant. So,
(| ) = = (| ).
The conditional expectation of e is zero because income and e are independent.
(| ) = 0 = 0.
(ii) Ag
ECON 360 Problem Set 3 Solutions
WOOLDRIDGE CHAPTER 2
2.1 (i) Income, age, and family background (such as number of siblings) are just a few
possibilities. It seems that each of these could be correlated with years of education. (Income
and education are
The Simple Linear
Regression Model
ECONOMETRICS (ECON 360)
BEN VAN KAMMEN, PHD
Outline
Definition.
Deriving the Estimates.
Properties of the Estimates.
Units of Measurement and Functional Form.
Expected Values and Variances of the Estimators.
Definition o
More on Specification
and Data Issues
ECONOMETRICS (ECON 360)
BEN VAN KAMMEN, PHD
Introduction
Most of the remaining lessons on OLS address problems with the 4th Gauss-Markov assumption
(the error terms mean independence from the regressors):
1 , . . . ,
Math, Stats, and
Mathstats Review
ECONOMETRICS (ECON 360)
BEN VAN KAMMEN, PHD
Outline
These preliminaries serve to signal to students what tools they need to know to succeed in
ECON 360 and refresh their familiarity with these tools. These are things you
Basic Regression with
Time Series Data
ECONOMETRICS (ECON 360)
BEN VAN KAMMEN, PHD
Introduction
This chapter departs from the cross-sectional data analysis, which has been the focus in the
preceding chapters.
Instead of observing a many (n) elements in a
Multiple Regression
with Qualitative
Information
ECONOMETRICS (ECON 360)
BEN VAN KAMMEN, PHD
Introduction
There is a lot of (relevant) information in data about the elements observed that is not in
quantitative form.
This chapter explores how that informa
Heteroskedasticity
ECONOMETRICS (ECON 360)
BEN VAN KAMMEN, PHD
Introduction
For pedagogical reasons, OLS is presented initially under strong simplifying assumptions.
One of these is homoskedastic errors, i.e., with constant variance, 2 .
Along with the
Carrying Out an
Empirical Project
ECONOMETRICS (ECON 360)
BEN VAN KAMMEN, PHD
Introduction
This lecture steps back from estimation and inference and reminds you to considerwhy youre
doing econometrics in the first place.
To test a theory about how the eco
OFFICE OF THE REGISTRAR
March 23, 2016
NAME: Qiao Huang
Ruling Zuo (Mother)
INVITATION OF GRADUATION
from
PURDUE UNIVERSITY
West Lafayette, Indiana
This is to certify that
QIAO HUANG
is scheduled to graduate in the Spring 2016 Commencement
Sunday May 13,
Multiple Regression
Analysis: Inference
ECONOMETRICS (ECON 360)
BEN VAN KAMMEN, PHD
Introduction
When you perform statistical inference, you are primarily doing one of two things:
Estimating the boundaries of an interval in which you suspect the populati
Multiple Regression
Analysis: Asymptotics
ECONOMETRICS (ECON 360)
BEN VAN KAMMEN, PHD
Introduction
There is not a lot of new material in this chapter, unless one wants to get into proofs of the
Central Limit Theorem, probability limits, and convergence in
News
Carcinogenicity of consumption of red and processed meat
In October, 2015, 22 scientists from
ten countries met at the International
Agency for Research on Cancer (IARC)
in Lyon, France, to evaluate the
carcinogenicity of the consumption
of red meat
ECON 360 First Exam Solutions
1. Suppose you are interested in estimating whether having a nicer car (measured by the log of the
price paid for the car) induces people to drive more. The dependent variable is the minutes spent
driving per month (measured
ECON 360 First Exam Solutions
1. Consider the multiple regression model containing three independent variables, under
Assumptions MLR.1 through MLR.4:
= 0 + 1 1 + 2 2 + 3 3 + .
You are interested in estimating the sum of the parameters on 1 and 2 ; call
Questions: Statistical Inference Exercise Part Deux
1. The model is:
= 0 + 1 + 2 + 3 + 4 + 5 +
6 + .
Null (and alternative) hypothesize about each parameter in this model.
See attached estimates.
2. Which regressors is/are statistically significant at th
ECON 360 In Class Exercise (2/20)
Refer to Table 6.1 in Wooldridge for the following questions.
1. What is the marginal effect of maternal smoking, measured in cigarettes per week, on
birth weight in ounces?
2. Is the effect in part 1 statistically signif
Questions: Quadratics and Interactions Exercise
1. The model is:
= 0 + 1 + 2 2 + 3 + 4 + 5 + 6 + ,
where WAR is a measure of (increasing in) a baseball pitchers performance, age is in
years, and FB refers to the pitchers fastball (the hardest-thrown and
Questions: Multivariate Statistics Exercise
These statistics are from Major League Baseball in 2012, observing each ( = 30) teams
win total and run-scoring (points) differential: our points minus our opponents points.
Variable
Obs
Mean
w
diff
30
30
81
0
S
3.8. We can confirm the following by using Table 3.2 in Wooldridge.
As I showed in class, the omitted variable bias formula is:
(1 , 2 )
1 = 1 + 2
.
(1 )
By definition, since ability is a productive attribute, 2 > 0, and the given information implies
tha
. reg sleep age totwrk
Source
SS
df
MS
Model
Residual
15155229.8
124084606
2
703
7577614.89
176507.263
Total
139239836
705
197503.313
sleep
Coef.
age
totwrk
_cons
2.923879
-.1490107
3469.201
Std. Err.
1.396712
.0167207
68.11787
t
2.09
-8.91
50.93
Number o
STATA Tutorial
In this course you will occasionally replicate results from academic papers using regression analysis and
the STATA software. This introduction will endow you with the basics of using STATA for that purpose.
1. All of the data used in this
Multiple Regression
Analysis: Further Issues
ECONOMETRICS (ECON 360)
BEN VAN KAMMEN, PHD
Introduction
Estimation (Ch. 3) and inference (Ch. 4) are the 2 fundamental skills one must perform when
using regression analysis.
This chapter adds a few embellishm
Multiple Regression
Analysis: Estimation
ECONOMETRICS (ECON 360)
BEN VAN KAMMEN, PHD
Outline
Motivation.
Mechanics and Interpretation.
Expected Values and Variances of the Estimators.
Motivation for multiple regression
Consider the following results of a
Midterm Exam 1
Econ 360 — Fall 2011
Professor Mumford Wednesday, October 5, 2011
mumford@purdue.edu
‘0 r M f '
YOUR NAME: m essw um ~ 0(6/
0 Answer all questions clearly and legibly.
0 Show all of your work in the space provided. Do not use additional she
ECON 360 Problem Set 5 Solutions
Instructions: Please write solutions to these problems by hand on separate paper and submit them in class. You
may collaborate with other students, but each student must submit his/her own responses. For the Stata
problem,
ECON 360 Problem Set 6 Solutions
Instructions: Please write solutions to these problems by hand on separate paper and submit
them in class. You may collaborate with other students, but each student must submit his/her
own responses. For the Stata problem,
ECON 360 Problem Set 8 Solutions
Instructions: Please write solutions to these problems by hand on separate paper and submit
them in class. You may collaborate with other students, but each student must submit his/her
own responses. The assignment is due
ECON 360 Problem Set 2 Solutions
Instructions: Please write solutions to these problems by hand on separate paper and submit
them in class. You may collaborate with other students, but each student must submit his/her
own responses. For the Stata problem,
ECON 360 Problem Set 3 Solutions
Instructions: Please write solutions to these problems by hand on separate paper and submit
them in class. You may collaborate with other students, but each student must submit his/her
own responses. For the Stata problem,