Econ 526
Spring 2013
Problem Set 4: Multiple Regression
This problem set will introduce you to running wage regressions and using dummy
variables in STATA. You will be using data from the National Survey of College
Graduates (NSCG). The data is available
Econ 526
Manopimoke
Spring 2013
Econometrics Problem Set #5
SOLUTIONS
Instructions:
Please write your answers legibly. No late assignments, no exceptions.
8.2.
(a) According to the regression results in column (1), the house price is expected to
increase
Simple Linear Regression Model
Well be working through the simple regression model, where we impose the
assumptions from the Classical Linear Regression Model. Define the following
variables:
y = the dependent variable;
x = the independent variable;
= th
Econ 526/ Manopimoke/ Fall 2012
Econometrics Practice Exam 2
1.
2.
Chapters 7-9, 11-12, 14
STATA: You need to be able to read and interpret STATA output.
1.
Suppose that there are threshold effects when examining the relationship between class
size and st
Econ 526/ Spring 2013
Manopimoke
Midterm 2 (Set A): Show and EXPLAIN your working for full credit! (75 points possible)
Question 1 (30 points)
Females, on average, are shorter and weigh less than males. One of your friends, who is a premed student, tells
Econ 526 / Manopimoke
Econometrics Problem Set #1
Solutions
Instructions:
Please write your answers legibly. No late assignments, no exceptions.
1. Faced with the question of determining the probability of obtaining either 0 heads, 1 head or 2
heads when
Econ 526/ Manopimoke
Spring 2013
Econometrics Problem Set #2
100 Points possible-SOLUTIONS
Instructions:
Please write your answers legibly. No late assignments, no exceptions.
1. Answer question 4.2 in your text book .
(a) Substituting Height 70, 65, and
Econ 526
Spring 2013
Econometrics Problem Set #3
1. Add variable labels to beauty course_eval intro nnenglish and then describe and
summarize your data. Below, report the mean of course_eval and the mean of
beauty. Interpret these numbers.
storage
variabl
Chapter 1
1. What kinds of questions do we care about in economics?
a. Stats are easy to lie about
b. Statistical arguments form the basis of social/political decision making
2. Quantitative v. qualitative data (and how to transform qualitative data into
Chapter 4
1. Know the terminology (e.g., which are dependent/independent variables, etc.)
a. Ordinary least squares
i. Hypothesis test again to see if the relationship or slope=0 or not
ii. H0 = y = 0
iii. H0 = 1 = 0
2. Interpreting coefficients/being abl
Chapter 3
1. Properties of estimators (e.g., unbiased, consistent)
a. Unbiasedness
i. The expectation of your estimator is what youre trying to estimate. E( y ) = y
E(Y1) = y
b. Consistency
i. As n gets big, our estimate gets close to what we are trying t
Chapter 2
1. Terms of probability (outcomes, sample space, etc.)
a. Random experiment the process of observing the outcome of a chance event
b. Elementary outcomes all possible events/results of random experiment
c. Sample space the set of all the element
Intro to Econometrics/Econ 526
Fall 2014/ Manopimoke
Review of Statistics
Policy question: What is the effect on test scores (or some other
outcome measure) of reducing class size by one student per class?
by 8 students/class?
We must use data to find out
Intro to Econometrics/Econ 526
Fall 2014/ Manopimoke
Review of Statistics
3.2 Hypothesis Testing
Making a decision based on the evidence at hand whether a certain
claim is true.
A.
Start by specifying the null and alternative hypotheses.
H0: = 0. Ha: 0 (a
Homework 6 solutions
11.6.
(a) For a black applicant having a P/I ratio of 0.35, the probability that the application will be
denied is ( 2.26 2.74 0.35 0.71) (0.59) 27.76%.
(b) With the P/I ratio reduced to 0.30, the probability of being denied is ( 2.26
Chapter 5
1. 1-sided and 2-sided hypothesis tests for regression coefficients (perform and know what the
results mean!)
2. Confidence intervals for regression coefficients
a. CI for 1 = cfw_
^
1
+ CV (SE
^
1 )
b. Example
i. Pollution (C02) and Production