2 Economists generally agree that an individual`s earnings are positively related to the knowledge and skills obtained through education and experience. Numerous studies show that, on average, people with more years of education do earn higher wages.
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Prof. Zhao
Lecture 21: Practice for Final Exam
Exercise 1:
1. To test for the racial discrimination in the mortgage application market, a researcher
proposed the following simple regression model:
approve = 0 + 1 white + u
where approve is an
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Prof. Zhao
Lecture 18: Dummy Variables (Ch7)
Most of the variables in our regression analysis have been quantitative. For example,
wage, education, house price, footage, number of bedrooms, math10, number of staff,
and enrollment all take num
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Prof. Zhao
Lecture 17: Review for Midterm II
Modified C4.9
In order to study the possible racial discrimination in the soda market, we use a
population model below, where psoda is the medium soda price (in dollars) in a zip code,
prpblck the
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Prof. Zhao
Lecture 16: OLS Asymptotics
So far, we have discussed a few finite sample properties of OLS estimators. In particular,
they are BLUE and normally distributed when the error term is normal. These properties
hold for any sample size
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Prof. Zhao
Lecture 15: The F-test for Testing Linear Restrictions
So far, we have discussed how to test on one single population parameter. We can
generalize our discussion to the case where we want to test altogether multiple
hypotheses, in
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Prof. Zhao
Lecture 13: Testing Hypotheses in Multiple Regressions
Testing Hypotheses: About a Single Parameter
Recall that in hypothesis testing, an alternative/research hypothesis is tested against a
null hypothesis. Depending on the type of
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Prof. Zhao
Lecture 14: Testing Hypotheses in Multiple Regressions (Continued)
HW #4: 4.2, 4.3, 4.4
The p-Values of t- test
Recall that p-value is defined as the probability that the test statistic takes a value at least
as extreme as the one
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Prof. Zhao
Lecture 12: Statistical Inference in Multiple/Simple Regressions (Ch4)
Previously we have studies some statistical properties of OLS estimators in multiple
regressions. In particular we analyzed their expected value and variance, w
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Prof. Zhao
Lecture 11: Examples of Multiple Regressions
HW #3: 3.4, C3.1, C3.2
Example 1: C3.2
price = 0 + 1 sqrft + 2 bdrms + u
Let us use this example to illustrate a few things important in multiple regression.
(1) Suppose you are a homeow
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Prof. Zhao
Lecture 7: More on Simple Regressions
HW2: C2.5, C2.7
Units of Measurement and Functional Form
So far we have focused on linear relationship between two variables. But linear
relationships are not general enough for all economic ap
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Prof. Zhao
Lecture 4: Examples of Simple OLS Regression and the Algebraic Properties of
OLS Statistics
HW1: 2.3, 2.4, 2.5
Example: Modified Problem 2.1
In order to study the relationship between a womans fertility and her education level, we
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Prof. Zhao
Lecture 20: Issues with OLS
HETEROSKEDASTICITY
For OLS estimators to be BLUE, one crucial assumption we have been assuming in our
multiple regression analysis is that the variance of the unobserved error is constant
conditional on