Question

1) Which of the following does not generally decrease the variance of the OLS estimator of...

1) Which of the following does not generally decrease the variance of the OLS estimator of slope βˆ1?

a) Increasing the variance of the error term, b) Increasing the sample size, c) None of the above, d) Increasing the variance of the independent variable

2) If the independent variable is a binary variable then which of the following is true?

a)β0 is a population mean for the group with a value of 1 for the independent variable,

b) β1 is the difference between two population means

c) β0 is the difference between two population means

d) β1 is a population mean for the group with a value of 0 for the independent variable

3) Which of the following is not a consequence of the 3 least squares assumptions

a) The OLS estimators are consistent.

b) The OLS estimators are unbiased.

c) The OLS estimators are approximately normally distributed in large samples.

d) The OLS estimators are efficient.

Math   Statistics-And-Probability   
0 0
Add a commentTranscribed image text
Next >

Homework Answers

Answer #1

Q.1) Option a) is correct.

If increasing the variance of the error term then generally does not decrease the variance of the OLS estimator of slope βˆ1 it will increase.

Q.2) Option c) is correct.

If the independent variable is a binary variable then is the difference between two population mean.

Q.3) Option c) is correct.

The least square estimates are linear, consistent as well as efficient but it is not necessory they are normally distribted in large samples .

0 0
Know the answer?
Your Answer:

Post as a guest

Your Name:

What's your source?

Earn Coins

Coins can be redeemed for fabulous gifts.

Log In

Sign Up

Not the answer you're looking for?
Ask your own homework help question
Similar Questions
1. The Central Limit Theorem A. States that the OLS estimator is BLUE B. states that...
1. The Central Limit Theorem A. States that the OLS estimator is BLUE B. states that the mean of the sampling distribution of the mean is equal to the population mean C. none of these D. states that the mean of the sampling distribution of the mean is equal to the population standard deviation divided by the square root of the sample size 2. Consider the regression equation Ci= β0+β1 Yi+ ui where C is consumption and Y is disposable...
1. Consider the bivariate model: Yi = β0+β1Xi+ui . Explain what it means for the OLS...
1. Consider the bivariate model: Yi = β0+β1Xi+ui . Explain what it means for the OLS estimator, βˆ 1, to be consistent. (You may want to draw a picture.) 2. (Circle all that applies) Which of the following regression functions is/are linear in the parameters a) Yi = β1 + β2 1 Xi b) Yi = β1 + β 3 2Xi c) Yi = β1 + β2Xi
Answer the following questions in technical or non-technical language. (a) What is the Central Limit Theorem?...
Answer the following questions in technical or non-technical language. (a) What is the Central Limit Theorem? (b) What does it mean for an estimator to be unbiased or consistent? (c) What is the difference between point estimators and interval estimators of parameters? (d) Under what conditions should we use t-tests rather than z-tests for population means? (e) Why are conjugate families of distributions convenient for Bayesian analysis?
Which of the following statements is correct regarding the implication of the existence of heteroscedasticity? A)...
Which of the following statements is correct regarding the implication of the existence of heteroscedasticity? A) The OLS estimator is biased. B) The OLS estimator is unbiased and still best. There is no other estimator with smaller variance. C) The OLS estimator is biased but the standard errors usually computed for the OLS estimator are correct. D) The standard errors usually computed for the OLS estimator are incorrect.
a. If ? ̅1 is the mean of a random sample of size n from a...
a. If ? ̅1 is the mean of a random sample of size n from a normal population with mean ? and variance ?1 2 and ? ̅2 is the mean of a random sample of size n from a normal population with mean ? and variance ?2 2, and the two samples are independent, show that ?? ̅1 + (1 − ?)? ̅2 where 0 ≤ ? ≤ 1 is an unbiased estimator of ?. b. Find the value...
Consider the following statements concerning confidence interval estimates: A. The use of the pooled variance estimator...
Consider the following statements concerning confidence interval estimates: A. The use of the pooled variance estimator when constructing a confidence interval for the difference between means requires the assumption that the population variances are equal. B. The width of a confidence interval estimate for the proportion, or for mean when the population standard deviation is known, is inversely proportional to the square root of the sample size. C. To determine the sample size required to achieve a desired precision in...
Discuss whether each of the following statements is correct or not. (a) A large t-value implies...
Discuss whether each of the following statements is correct or not. (a) A large t-value implies a low p-value. (b) The law of iterated expectations implies that if the conditional mean of Y given X is zero, then the mean of Y is zero. (c) A sample correlation of 0.97 between the regressors causes OLS estimators to be biased. (d) Measurement error in the independent variable causes OLS estimators to be biased.
which of the following is an unbiased point estimator for the expected value of any sampled...
which of the following is an unbiased point estimator for the expected value of any sampled random variables? a) the sample varlance b) the p-value c) the sample mean d) the margin of error
1) Which is NOT a fundamental assumption of OLS (Ordinary Least Squares)? a)       The...
1) Which is NOT a fundamental assumption of OLS (Ordinary Least Squares)? a)       The regression model is nonlinear in the coefficients and error term.   b)       Observations of the error term are uncorrelated with each other.    c)    No independent variable is a perfect linear function of any other explanatory variables.    d)   The error term has homoscedasticity. e)   All independent variables will be uncorrelated with the error term. ----------------------------------------------------------------------------------------------------------------------------------------------- ----------------------------------------------------------------------------------------------------------------------------------------------- 2) You test a model that...
1. When the error-terms are heteroskedastic, then: a) WLS is more efficient than OLS in large...
1. When the error-terms are heteroskedastic, then: a) WLS is more efficient than OLS in large samples, if the functional form of the heteroskedasticity is known. b) OLS coefficients are biased. c) OLS is still BLUE but t and F distributions are invalid. d) there are only two solutions: either use WLS if the functional form of the heteroskedasticity is known or use GLS if the functional form of the heteroskedasticity is known. e) None of the above 2. Which...
ADVERTISEMENT
Need Online Homework Help?

Get Answers For Free
Most questions answered within 1 hours.

Ask a Question
ADVERTISEMENT