![[3] TRUE or FALSE: In the presence of autocorrelation, the OLS estimators remain unbiased but are no longer efficient. [4] TR](http://img.homeworklib.com/questions/6dbcba60-79a1-11ea-b5b2-530272f056f6.png?x-oss-process=image/resize,w_560)
Homework Answers
3. True.
OLS estimators are still unbiased but no longer efficient. They no longer have the minimum variance.
4. False.
Eatimated OLS Variances are biased. They underestimate the true variance.
5. True.
They are all time series model.
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[3] TRUE or FALSE: In the presence of autocorrelation, the OLS estimators remain unbiased but are...
Answer each question by writing TRUE or FALSE 1. For OLS estimators to be linear the...
Answer each question by writing TRUE or FALSE 1. For OLS estimators to be linear the explanatory variables must be variable, non- stochastic and fixed in repeated samples. Under the conditions of perfect multicollinearity, the OLS estimators are not unique. The presence of heteroskedasticity causes the OLS method to overestimate the variances 2. 3. of the parameters. The Breusch-Godfrey LM test is applicable when a lagged dependent variable is used. If we include a non-influential variable in an equation the...
3. We obtain autocorrelation function of residuals of the five autoregressive models: AR(1), AR(2), AR(3), AR(4)...
3. We obtain autocorrelation function of residuals of the five autoregressive models: AR(1), AR(2), AR(3), AR(4) and AR(5). Choose a model that performs reasonably well, according to the plots of autocorrelation function. Explain the reason (no more than 20 words.) Autocorrelation function for AR(1) model Series ar1$residuals 1.0 RO 0.6 ACF 0.4 -0.2 0.0 0.2 0 5 10 15 Lag Autocorrelation function for AR(2) model Serles ar2$residuals 1.0 RO 0.6 ACF 0.4 -0.2 0.0 0.2 0 5 10 15 Lag...
5.This is a copy of the original series moved forward two time periods A. Lagged series...
5.This is a copy of the original series moved forward two time periods A. Lagged series with no lag B. Lagged series with lag-1 C. Lagged series with lag-2 D.None of the above 6. This reflects swings in the series, where high values are immediately followed by low values and vice versa. A.Negative lag-1 autocorrelation B. Strong autocorrelation C. Positive lag-1 autocorrelation D.All the above 7.This approach is generally taken to take advantage of auto correlation A. Directly build autocorrelation...
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...
Answer each question by writing T or F When selecting models using the Akaike Information Criterion...
Answer each question by writing T or F When selecting models using the Akaike Information Criterion (AIC) we select the model that minimises the statistic. 1. 2. When imperfect multicollinearity exists among two or more explanatory variables, and 3. The Breusch-Pagan LM test statistic follows the F-distribution. 4. If a regression model suffers from autocorrelation the OLS estimators are inefficient and 5. If we include a non-influential variable in an equation the OLS estimators will be biased 6. We can...
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...
Question 3 True/False/Explain 1. The variance of the OLS estimator of the coefficient of a certain...
Question 3 True/False/Explain 1. The variance of the OLS estimator of the coefficient of a certain variable X; in a regression is higher, the higher is the degree of collinearity between that variable and the other regressors included in the model 2. Suppose that we estimated the following hourly wage equation n(wage) .092educ + .0041ехреr + (007) 022tenure 284 (0017) (.104) (003) where the numbers in parentheses are estimated standard errors. Assuming that the classical normal linear regression model holds,...
Imagine that you regressed the earnings of individuals on a constant, a binary variable (“Male”) which...
Imagine that you regressed the earnings of individuals on a constant, a binary variable (“Male”) which takes on the value of 1 for males and is 0 otherwise, and another binary variable (“Female”) which takes on the value of 1 for female and is 0 otherwise. Because females typically earn less than males, you would expect: Group of answer choices autocorrelation or serial correlation to be a serious problem. the estimated coefficient for Male to have a positive sign, and...
Need help with stats true or false questions Decide (with short explanations) whether the following statements are true or false a) We consider the model y-Ao +A(z) +E. Let (-0.01, 1.5) be a 95% con...
Need help with stats true or false questions
Decide (with short explanations) whether the following statements are true or false a) We consider the model y-Ao +A(z) +E. Let (-0.01, 1.5) be a 95% confidence interval for A In this case, a t-test with significance level 1% rejects the null hypothesis Ho : A-0 against a two sided alternative. b) Complicated models with a lot of parameters are better for prediction then simple models with just a few parameters c)...
1. Let X and Y be two random variables.Then Var(X+Y)=Var(X)+Var(Y)+2Couv(X,Y). True False 2. Let c be...
1. Let X and Y be two random variables.Then Var(X+Y)=Var(X)+Var(Y)+2Couv(X,Y). True False 2. Let c be a constant.Then Var(c)=c^2. True False 3. Knowing that a university has the following units/campuses: A, B , the medical school in another City. You are interested to know on average how many hours per week the university students spend doing homework. You go to A campus and randomly survey students walking to classes for one day. Then,this is a random sample representing the entire...
Answer each question by writing TRUE or FALSE 1. For OLS estimators to be linear the explanatory variables must be variable, non- stochastic and fixed in repeated samples. Under the conditions of perfect multicollinearity, the OLS estimators are not unique. The presence of heteroskedasticity causes the OLS method to overestimate the variances 2. 3. of the parameters. The Breusch-Godfrey LM test is applicable when a lagged dependent variable is used. If we include a non-influential variable in an equation the...
3. We obtain autocorrelation function of residuals of the five autoregressive models: AR(1), AR(2), AR(3), AR(4) and AR(5). Choose a model that performs reasonably well, according to the plots of autocorrelation function. Explain the reason (no more than 20 words.) Autocorrelation function for AR(1) model Series ar1$residuals 1.0 RO 0.6 ACF 0.4 -0.2 0.0 0.2 0 5 10 15 Lag Autocorrelation function for AR(2) model Serles ar2$residuals 1.0 RO 0.6 ACF 0.4 -0.2 0.0 0.2 0 5 10 15 Lag...
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...
Answer each question by writing T or F When selecting models using the Akaike Information Criterion (AIC) we select the model that minimises the statistic. 1. 2. When imperfect multicollinearity exists among two or more explanatory variables, and 3. The Breusch-Pagan LM test statistic follows the F-distribution. 4. If a regression model suffers from autocorrelation the OLS estimators are inefficient and 5. If we include a non-influential variable in an equation the OLS estimators will be biased 6. We can...
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...
Question 3 True/False/Explain 1. The variance of the OLS estimator of the coefficient of a certain variable X; in a regression is higher, the higher is the degree of collinearity between that variable and the other regressors included in the model 2. Suppose that we estimated the following hourly wage equation n(wage) .092educ + .0041ехреr + (007) 022tenure 284 (0017) (.104) (003) where the numbers in parentheses are estimated standard errors. Assuming that the classical normal linear regression model holds,...
Need help with stats true or false questions
Decide (with short explanations) whether the following statements are true or false a) We consider the model y-Ao +A(z) +E. Let (-0.01, 1.5) be a 95% confidence interval for A In this case, a t-test with significance level 1% rejects the null hypothesis Ho : A-0 against a two sided alternative. b) Complicated models with a lot of parameters are better for prediction then simple models with just a few parameters c)...
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