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(3)What are the exact values of R² and adjusted R2 in (1)? Explain your answer intuitively.

(4) Demonstrate the following statistic follows a (Student) t-distribution,

a

se(a)

Econometric Methods (AF6208)

Dr. Steven X.. Wei

where the first term of the numerator is the OLS estimator of a and the denominator is the estimated standard deviation of a

and a is the true value. [You can check any reference in your textbook, slides, internet, and other reference books. Comments:

Through the exercise, you should understand the unconditional analysis is actually a special case of conditional analysis! This

exercise sets up a link between a conditional analysis and an unconditional analysis! It is also a good exercise for your

understanding the intuition and mathematics behind a simple linear regression model. To some extent, you understand that there

is a link between the results of your descriptive statistics and those in your regression models when you read reference papers or

write your own thesis.].

Q3. Consider a special case of simple linear regression model,

Yi = a + u;

i = 1, 2,…,n

?

where u; ~N(0, o?).

Answer the following two questions:

(1) Using the FOC to work out the OLS estimate of a, and then construct the OLS estimate of o?? [Pay special attention to the

divisor” of the estimate to make sure that your estimate of o is unbiased).

(2) Demonstrate mathematically that a , the OLS estimator of a, is unbiased, and then calculate its variance and estimated standard

deviation, i.e., Var( a ) and Sel a ).

(3)What are the exact values of R2 and adjusted R2 in (1)? Explain your answer intuitively.

(4) Demonstrate the following statistic follows a (Student) t-distribution,

>

a

a

se(a)

(3) Through the analysis, you should understand that in your thesis, missing a control variable is in fact a serious problem in principle.

Investigate how the missing variable problem is dealt with or mitigated in research (or more clearly in published research papers).

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Explanation & Answer:

3 Questions

Tags:

standard deviation

Statistical analysis

conditional analysis

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