Consider the model, Yt = 0.8 + 0.1 Yt-1 +0.5 X1,t + 1.7 X2,t + Ut....
Consider the model, Yt = B0 + B1 X1,t + B1 X2,t + Ut, and this is estimated using OLS with 350 observations. However, it is suspected autocorrelation is present. You compute the DW statistic as 0.891. The critical values for this model are: dL = 1.741 and dU = 1.764. What is your decision? A. Reject the null. B. Fail to reject the null. C. Undetermined or inconclusive.
Consider the model, Yt = BO+B1 X1,t + B1 X2,t + Ut, and this is estimated using OLS with 250 observations. However, it is suspected autocorrelation is present. You compute the DW statistic as 1.997. The critical values for this model are: dL = 1.692 and du = 1.724. What is your decision? A. Reject the null. B. Fail to reject the null. C. Undetermined or inconclusive.
Consider the model, Yt = Bo + B1 X1,1+B1 X2,t + Ut, and this is estimated using OLS with 350 observations. You run some tests with the following results: DWH fails to reject, BG fails to reject, and White test rejects. Select the combination of approaches for the most appropriate estimation of the coefficients. A. Use 2 SLS B. Heteroskedastic correction using X2,t only. c. Use Newey-West HAC. D. Use OLS. Heteroskedastic correction using X1,t only. F. Use White's heteroskedastic-consistent...
• 1. What are the quarterly growth rates (Percentage Change From Preceding Period in Real Gross Domestic Product) for the U.S. economy for the last six quarters? Report those numbers in your submission 2. What is the average of those 6 quarters? . 3. Is the average of those growth rates above or below the long-run U.S. annual growth rate of 3.5 percent? Bureau of Economke Analysis Table 1.1.1. Percent Change From Preceding Period in Real Gross Domestic Product Percent...
Python Pandas, Series and DataFrame Question (NO Loops, No If Statements, No List Comprehensions) The file bank.csv contains data about bank customers. The last column ('Personal Loan') indicates whether or not the customer was approved for a personal loan or not. Write a function named loan_by_zip that accepts 3 parameters: a file name, a minimum number of records, and a percentage approval rate. The function should return a DataFrame of those zip codes for which we meet the minimum number...
I ONLY NEED HELP WITH PART OF PART "B"
I've figured out the test statistic is -1.73 and the degrees of
freedom are 5. However, I'm having a hard time finding the P value
via the chart (which I'm required to learn how to do).I think the
chart immediately bellow this is the one used to find the p-value.
However, I know at least one (or more) of the charts bellow is
what's used. Please let me know which chart...
I ONLY NEED HELP WITH PART OF PART "B"
I've figured out the test statistic is -1.73 and the degrees of
freedom are 5. However, I'm having a hard time finding the P value
via the chart (which I'm required to learn how to do).I think the
chart immediately bellow this is the one used to find the p-value.
However, I know at least one (or more) of the charts bellow is
what's used. Please let me know which chart...