CHAPTER
4
Exercise Solutions
60
Chapter 4, Exercise Solutions, Principles of Econometrics, 3e 61
EXERCISE 4.1
ei2
2
( yi y )
(a)
R2 = 1
(b)
To calculate R 2 we need
( yi y )
2
=1
182.85
= 0.71051
631.63
( yi y )
2
,
= yi2 N y 2 = 5930.94 20 16.0352 =
ECO 321 - Introduction to Econometrics
Last points and midterm tips
Flora Leventis
Hunter College - Fall 2013
October 18, 2013
Flora Leventis (Hunter College - Fall 2013)
ECO 321 - Introduction to Econometrics
October 18, 2013
1/8
A note on model specicat
Economic Statistics II Solutions - Homework Assignment 4
Use the data set usmacro.dta that contains the monthly US unemployment rate [%]: Stata's variable name unemp, from 1984m1 to 2010m3. Define U nempt to be the unemployment rate. Assume that the error
Undertake the following exercise using Stata. You should track your work during class time
somehow (either piece by piece or use a log fileProf. Roeper should have shown you how to
do this). At the end of class, compile your results into a separate text f
ECO 321 - Introduction to Econometrics
More on the error variance and the variance of and hypothesis testing
(dierent types of tests)
Flora Leventis
Hunter College - Fall 2013
October 1, 2013
Flora Leventis (Hunter College - Fall 2013)
ECO 321 - Introduct
Final Exam Review Sheet for Eco321
Topic: Empirical Research
Pros
Prove experiments using observations.
Concrete evidence
Quantifiable numerical data that can be measured
Cons
Certain data cant be measured omitted variables Example: Ability
Biasednes
ECO 321: Answers to Problem Set 2
Instructor: Flora Leventis - Hunter College Fall 2013
October 19, 2013
Question 1:
1. 1 is the coecient on cigsi . As cigs increases by 1, bweight decreases by 1 , or 0.514; This is because
1 = -0.514, and is a negative v
Economic Statistics II Solution - Homework Assignment 3
Part-I Using the data Growth.dta, run three regressions of Growth on Regression A: T radeShare and Y earsSchool Regression B: T radeShare and ln(Y earsSchool) Regression C: T radeShare, ln(Y earsScho
ECO 321 - Introduction to Econometrics
Multiple Linear Regression Model cont.
Flora Leventis
Hunter College - Fall 2013
October 8, 2013
Flora Leventis (Hunter College - Fall 2013)
ECO 321 - Introduction to Econometrics
October 8, 2013
1 / 39
Multiple Regr
BOSTON COLLEGE
Department of Economics
EC 228 Econometrics, Prof. Baum, Ms. Yu, Fall 2003
Problem Set 4 Solutions
Problem sets should be your own work. You may work together with
classmates, but if youre not guring this out on your own, you will eventuall
CHAPTER 1
SOLUTIONS TO PROBLEMS 1.1 (i) Ideally, we could randomly assign students to classes of different sizes. That is, each student is assigned a different class size without regard to any student characteristics such as ability and family background.
Examples of Questions on Regression Analysis:
1.
Suppose that a score on a final exam depends upon attendance and unobserved factors that
affect exam performance (such as student ability). Then,
.
When would you expect this model to satisfy the assumption
Chapter 7
7.1 The null hypothesis that 1 = 0 can be tested using the t-statistic for 1 as described in
Key Concept 7.1. Similarly, the null hypothesis that 2 = 0 can be tested using the tstatistic for 2 . The null hypothesis that 1 = 0 and 2 = 0 can be te
Chapter 6
6.1 It is likely that 1 will be biased because of omitted variables. Schools in more affluent
districts are likely to spend more on all educational inputs and thus would have smaller
class sizes, more books in the library, and more computers. Th
Chapter 5
5.1. The p-value for a two-sided test of H 0 : = 0 using an i.i.d. set of observations Y i , i =
1, . . . , n can be constructed in three steps: (1) compute the sample mean and the
standard error SE( Y ); (2) compute the t-statistic for this sam
Chapter 4
4.1 1 is the value of the slope in the population regression. This value is unknown. 1 (an
estimator) gives a formula for estimating the unknown value of 1 from a sample.
Similarly, u i is the value of the regression error for the ith observatio
ECON 570
Fall, 2010
Solution to
HW - 2
Instructor:
Saraswata Chaudhuri
Problem 1. [Points = 4] Suppose that a researcher, using data on class size CS average
test scores from 100 third-grade classes, estimates the OLS regression,
T estScore = 520.4 5.82 C
Guideline to Homework Assignments and Answering Statistical/Econometrics questions
in general.
As I mentioned earlier, how you present your answers and the language/phrasing you
use is very important. This is true not only for this course (or other course
CHAPTER
3
Exercise Solutions
31
Chapter 3, Exercise Solutions, Principles of Econometrics, 3e 32
EXERCISE 3.1
(a)
The required interval estimator is b1 tc se(b1 ) . When b1 = 83.416, tc = t( 0.975,38) = 2.024
and se(b1 ) = 43.410, we get the interval esti
Notes/comments on the answers to problem set 2
1. It is always to better to write out the test statistics and your calculation; this way you can
avoid simple mistakes. Do not just write down the final number, rather show your work.
This is especially true
Guideline to Homework Assignments and Answering Statistical/Econometrics questions
in general.
As I mentioned earlier, how you present your answers and the language/phrasing you
use is very important. This is true not only for this course (or other course
Exercise 4
name: <unn am ed>
log: C:\U se rs\ Fl ora \D ocume nts\ EC O32 1_ Hun te r\ECO 321 Xf er\ Ec on St atsII \Pr
> oblem Sets\Wool dr idg e Dat as ets ( Full D own lo ad) \P S2_ex ercise 4.s mc l
log type: smcl
opened on: 13 Oct 2013, 15:12:34
. us
Econ 360 Econometrics
OLS Inference
Huanren (Warren) Zhang
Krannert School of Management
Purdue University
February 5, 2013
Huanren Zhang (Purdue University)
Econometrics Chapter 4
February 5, 2013
1 / 58
Introduction
We have talked about how to obtain OL
ECO 321: Problem Set 2 - Due 10/18/2013
Instructor: Flora Leventis - Hunter College Fall 2013
October 12, 2013
Guidelines: For this particular assignment you will work on your own and
not into groups. You will need to submit a hard copy of your answers du
The Simple Regression Model
y = 0 + 1x + u
Some Terminology
In the simple linear regression model,
where y = 0 + 1x + u, we typically refer to
y as the
Dependent Variable, or
Left-Hand Side Variable, or
Explained Variable, or
Regressand
Some Terminology,
c Material based in part on Hiroshi Morita, 2010
ECO 321 - Introduction to Econometrics
Simple Linear Regression Model - Ch.4
Flora Leventis
Hunter College - Fall 2013
September 17, 2013
Flora Leventis (Hunter College - Fall 2013)
ECO 321 - Introduction t
Chapter 6: Linear Regression with Multiple Regressors
Multiple Choice for the Web
1)
In the multiple regression model, the adjusted R2, R 2
a.
b.
c.
d.
2)
cannot be negative.
will never be greater than the regression R2.
equals the square of the correlati