Homework Answers
Answer- 6 The correct option is c.) the distribution of beta j hat collapses to the single point beta j.
An estimator is said to be consistent if it converges to the true value of the parameter as the sample size tends to infinity.
Thus , the correct option is C.
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6. If 3,, an unbiased estimator of B,, is also a consistent estimator of B, then...
6. If 3, an unbiased estimator of 8,, is also a consistent estimator of 8., then as the sample size tends to infinit...
6. If 3, an unbiased estimator of 8,, is also a consistent estimator of 8., then as the sample size tends to infinity a. the distribution of 8, collapses to a single value of zero b. the distribution of 8, diverges away from a single value of zero c. the distribution of 3, collapses to the single point 8 d. the distribution of 8, diverges away from 3
1. If OLS estimators satisfy asymptotic normality, it implies that a. they are approximately normally distributed b. th...
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...
To show an estimator can be consistent without being unbiased or even asymptotically unbiased, consider the...
To show an estimator can be consistent without being unbiased or even asymptotically unbiased, consider the following estimation procedure: To estimate the mean of a population with the finite variance σ 2 , we first take a random sample of size n . Then, we randomly draw one of n slips of paper numbered from 1 through n , and • if the number we draw is 2, 3, ··· , or n , we use as our estimator the...
To show an estimator can be consistent without being unbiased or even asymptotically unbiased, consider the...
To show an estimator can be consistent without being unbiased or even asymptotically unbiased, consider the following estimation procedure: To estimate the mean of a population with the nite variance 2, we rst take a random sample of size n. Then, we randomly draw one of n slips of paper numbered from 1 through n, and if the number we draw is 2, 3, , or n, we use as our estimator the mean of the random sample; otherwise, we...
10.41] To show an estimator can be consistent without being unbiased or even asymptotically unbiased, consider...
10.41] To show an estimator can be consistent without being unbiased or even asymptotically unbiased, consider the following estimation procedure: To estimate the mean of a population with the finite variance σ2, we first take a random sample of size n. Then, we randomly draw one of n slips of paper numbered from 1 through n, and if the number we draw is 2, 3, ..., orn, we use as our estimator the mean of the random sample; otherwise, we...
To show that an estimator can be consistent without being unbiased or even asymptotically the finite...
To show that an estimator can be consistent without being unbiased or even asymptotically the finite variance σ, we first take a random sample of size n. Then we randomly draw one of n slips of paper numbered from 1 through n, and if the number we draw is 2, 3,.., or n, we use as our estimator the mean of the random sample; otherwise, we use the estimate n2. Show that this estimation procedure is (a) consistent; (b) neither...
6. In Problem 1, show that θ2 is a consistent estimator for θ. Deduce that Y(n) is a consistent e...
Please answer as neatly as possible.
Much thanks in advance!
Question 1:
6. In Problem 1, show that θ2 is a consistent estimator for θ. Deduce that Y(n) is a consistent estimator for θ and also asyınpt○tically unbiased estimator for θ. 1. Let Yi, ½, . . . ,y, denote a random sample from an uniform distribution on the interval (0,0). We have seen that (1) and 62 Ym are unbiased estimators for 0. Find the efficiency of 6 relative...
To show that an estimator can be consistent without being unbiased or even asymptotically unbiased, consider...
To show that an estimator can be consistent without being unbiased or even asymptotically unbiased, consider the following estimation procedure: To estimate the mean of a population with randomly draw o slips of paper numbered from 1 through n, and if the number we draw is 2, 3,.. .or n, we use as our estimator the mean of the random sample; otherwise, we use the estimate n2. Show that this estimation procedure is (a) consistent; (b) neither unbiased nor asymptotically...
Which of the following statements is true? (a) If the calculated value of F statistic is...
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...
6. If 3, an unbiased estimator of 8,, is also a consistent estimator of 8., then as the sample size tends to infinity a. the distribution of 8, collapses to a single value of zero b. the distribution of 8, diverges away from a single value of zero c. the distribution of 3, collapses to the single point 8 d. the distribution of 8, diverges away from 3
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...
10.41] To show an estimator can be consistent without being unbiased or even asymptotically unbiased, consider the following estimation procedure: To estimate the mean of a population with the finite variance σ2, we first take a random sample of size n. Then, we randomly draw one of n slips of paper numbered from 1 through n, and if the number we draw is 2, 3, ..., orn, we use as our estimator the mean of the random sample; otherwise, we...
To show that an estimator can be consistent without being unbiased or even asymptotically the finite variance σ, we first take a random sample of size n. Then we randomly draw one of n slips of paper numbered from 1 through n, and if the number we draw is 2, 3,.., or n, we use as our estimator the mean of the random sample; otherwise, we use the estimate n2. Show that this estimation procedure is (a) consistent; (b) neither...
Please answer as neatly as possible.
Much thanks in advance!
Question 1:
6. In Problem 1, show that θ2 is a consistent estimator for θ. Deduce that Y(n) is a consistent estimator for θ and also asyınpt○tically unbiased estimator for θ. 1. Let Yi, ½, . . . ,y, denote a random sample from an uniform distribution on the interval (0,0). We have seen that (1) and 62 Ym are unbiased estimators for 0. Find the efficiency of 6 relative...
To show that an estimator can be consistent without being unbiased or even asymptotically unbiased, consider the following estimation procedure: To estimate the mean of a population with randomly draw o slips of paper numbered from 1 through n, and if the number we draw is 2, 3,.. .or n, we use as our estimator the mean of the random sample; otherwise, we use the estimate n2. Show that this estimation procedure is (a) consistent; (b) neither unbiased nor asymptotically...
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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