Econometrics, Spring 2016
In-Class Exercise 2/2/16 or 2/4/16: Introduction to Stata
To be used with the cps_small.dta example file, available on Blackboard
Datasets
All datasets used in class and for homework assignments will be posted to blackboard eithe

Chapter 4
1. Assumption MLR.6 (Normality of error terms)
2. Theorem 4.1 (t-distribution for standardized estimators)
Hypothesis Testing Procedure
1.Determine the null and alternative hypothesis
2.Specify the test statistic and its distribution if the null

ECON 5336 - Spring 2016
Problem Set 1
Due Date is Feb 20th at noon.
Instructions: You may work together on these questions, but all questions must be written up separately
and evidence that this has not occurred will be subject to UTAs plagiarism policy.

Econometrics - Spring 2016 - Problem Set 4
Malcolm Kass
Harshnil Chawda
A
0
5.0e-06
Density
1.0e-05
1.5e-05
Histogram of sprice
0
200000
400000
600000
selling price of home, dollars
800000
The histogram is Rightly skewed
The density value is very less as

Econometrics - Spring 2016 - Problem Set 3
Malcolm Kass
Harshnil -1001239376
Q1
A
Interpretation of Beta1 and Beta3
Interpretation of Beta1
If the highest degree earned is high school diploma than the average increase in pizza
prices will be 90.79$ as com

Economists may like to know how responsive/elastic the quantity demanded for a good is in response to a change in
the price of another good. For example, if the price of CD players decreases, what will happen to the quantity
demanded for CDs? Well, we can

Econometrics - Spring 2016 - Problem Set 2
Professor: Malcolm Kass
Solution: Harshnil Chawda (1001239376)
Due date is March 5th at noon
Q1
The longley data is a famous data set that was used to construct employment equations.
These data have the following

Problem Set 1.
Instructions: You may work together on these questions, but all questions must be
written up separately and evidence that this has not occurred will be subject to UTAs
plagiarism policy. Throughout, all work leading to your answers must be

1. Zero Conditional mean assumption
The explanatory variable must
not
contain information about the
mean
of the unobserved factors
2. figure 2.1
3. OLS Estimator formulas
4. Simple OLS: fitting a line that minimizes the sum of the residual squares.
Note t