Homework Answers
Solution:
Asymptotic normality means that if more and more probability distributions are drawn from the data, they converge to a normal distribution. Also, it means that as more and more sample is included (as sample size increases), the distribution of a data converges to that of a normal distribution.
Further, since increased and large sample size involved, (b) cannot be correct, hence eliminated.
We are talking about normal distribution and not standard normal distribution such that mean be constant at 0 and variance be sigma squared, hence option (c) eliminated.
Option (d) is not a feature of any distribution in general, thus easily eliminated.
Thus, from all above we can conclude that the correct option is (a) OLS estimators are approximately normally distributed in large enough sample sizes, if they satisfy asymptotic normality.
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1. If OLS estimators satisfy asymptotic normality, it implies that a. they are approximately normally distributed...
1. If OLS estimators satisfy asymptotic normality, it implies that a. they are approximately normally distributed...
1. If OLS estimators satisfy asymptotic normality, it implies that a. they are approximately normally distributed in large enough sample sizes b. they are approximately normally distributed in samples with less than 10 observations c. they have a constant mean equal to zero and variance equal to a d. they have a constant mean equal to one and variance equal to a
1. If OLS estimators satisfy asymptotic normality, it implies that a they are approximately normally distributed...
1. If OLS estimators satisfy asymptotic normality, it implies that a they are approximately normally distributed in large enough sample sizes b. they are approximately normally distributed in samples with less than 10 observations c. they have a constant mean equal to zero and variance equal to a d. they have a constant mean equal to one and variance equal to o
1. If OLS estimators satisfy asymptotic normality, it implies that a they are approximately normally distributed...
1. If OLS estimators satisfy asymptotic normality, it implies that a they are approximately normally distributed in large enough sample sizes b. they are approximately normally distributed in samples with less than 10 observations c. they have a constant mean equal to zero and variance equal to a d. they have a constant mean equal to one and variance equal to o
1. If OLS estimators satisfy asymptotic normality, it implies that a they are approximately normally distributed...
1. If OLS estimators satisfy asymptotic normality, it implies that a they are approximately normally distributed in large enough sample sizes b. they are approximately normally distributed in samples with less than 10 observations c. they have a constant mean equal to zero and variance equal to a d. they have a constant mean equal to one and variance equal to o
1. If OLS estimators satisfy asymptotic normality, it implies that a they are approximately normally distributed in...
1. If OLS estimators satisfy asymptotic normality, it implies that a they are approximately normally distributed in large enough sample sizes b. they are approximately normally distributed in samples with less than 10 observations c. they have a constant mean equal to zero and variance equal to a d. they have a constant mean equal to one and variance equal to o
1. If OLS estimators satisfy asymptotic normality, it implies that a. they are approximately normally distributed b. th...
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1. If OLS estimators satisfy asymptotic normality, it implies that a. they are approximately normally distributed in large enough sample sizes b. they are approximately normally distributed in samples with less than 10 observations c. they have a constant mean equal to zero and variance equal to a d. they have a constant mean equal to one and variance equal to a
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1. If OLS estimators satisfy asymptotic normality, it implies that a they are approximately normally distributed in large enough sample sizes b. they are approximately normally distributed in samples with less than 10 observations c. they have a constant mean equal to zero and variance equal to a d. they have a constant mean equal to one and variance equal to o
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1. If OLS estimators satisfy asymptotic normality, it implies that a. they are approximately normally distributed b. they are approximately normally distributed in samples with less than 10 observations large enough sample sizes c. they have a constant mean equal to zero and variance equal to d. they have a constant mean equal to one and variance equal to o 2 In a multiple regression model, the OLS estimator is consistent if a. there is no correlation between the dependent...
5. Asymptotic normality In large samples, even if the error term is not normally distributed, we can still compute approximately valid confidence intervals under the Gauss- Markov assumptions True False
Which of the following statements is true? (a) If the calculated value of F statistic is higher than the critical value, we reject the alternative hypothesis in favor of the null hypothesis. (b) The F statistic is always nonnegative as SSR, is never smaller than SSRur. (C) Degrees of freedom of a restricted model is always less than the de- grees of freedom of an unre- stricted model. (d) The F statistic is more flexible than the t statistic to...
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