Assume that, using 65 observations of the time series x you estimate the AR(2) model,x=0.2+0.32.x,-+0.41x,2and you test for autocorrelation up to order 7 using an auxiliary regression of the fitted residuals. Your Breusch-Godfrey test for autocorrelation has avalue of 31.15, what is the R2 from your auxiliary regression correct to 3 significant figures?0.4940.4790.5560.537

From the given information, xt=0.2+0.32xt-1+0.41xt-2+ut There are 65 observations for the time…

Answered: Assume that, using 65 observations of…

MATLAB: An Introduction with Applications

6th Edition

ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

Chapter1: Starting With Matlab

Section: Chapter Questions

Problem 1P

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Given the residuals squared derived from the regression: Marks = ƒ(Study hours) Use the information from the following auxiliary regression (table attached) to conduct the Park test to detect for the presence of heteroscedasticity at a = 5%.
Suppose that you plot the residuals from a regression of GDP on the unemployment rate and you get Figure 1. You would conclude that the error terms are Select one: a. definitely autocorrelated. b. possibly autocorrelated and you would perform a correction for heteroskedasticity. c. possibly autocorrelated and you would perform a formal test for autocorrelation. d. likely not autocorrelated.
In running a regression of the retunrs of stock XYZ against the returns on the market, the Std for the returns of stock XYZ is 20% and that of the market returns is 15%. If the estimated beta is found to be 0.75 : What is the maximum possible value of beta given that the standar deivation of the returns of stock XYZ is 20% and those of the market is 15% ?
The following results are from data concerning the amount withdrawn from an ATM machine based on the amount of time spent at the ATM machine (SECONDS) and the gender, FEMALE (dummy variable = 1 for females and = 0 for males) and an interaction term, SECONDS*FEMALE Based on the regression results, what is the predicted amount withdrawn for a male who spends 20 at the ATM machine? (please express your answer using 1 decimal places)
Suppose that a regression was run with three independent variables and 30 observations. The DurbinWatson statistic was 0.50. Test the hypothesis that there was no autocorrelation. Compute an estimate of the autocorrelation coefficient if the evidence indicates that there was autocorrelation. a. Repeat with the Durbin-Watson statistic equal to 0.80. b. Repeat with the Durbin-Watson statistic equal to 1.10. c. Repeat with the Durbin-Watson statistic equal to 1.25. d. Repeat with the Durbin-Watson statistic equal to 1.70.
Suppose that a regression was run with two independent variables and 28 observations. The Durbin-Watson statistic was 0.50. Test the hypothesis that there was no autocorrelation. Compute an estimate of the autocorrelation coefficient if the evidence indicates that there was autocorrelation. a. Repeat with the Durbin-Watson statistic equal to 0.80. b. Repeat with the Durbin-Watson statistic equal to 1.10. c. Repeat with the Durbin-Watson statistic equal to 1.25. d. Repeat with the Durbin-Watson statistic equal to 1.70.
Suppose an appliance manufacturer is doing a regression analysis, using quarterly time-series data, of the factors affecting its sales of appliances. A regression equation was estimated between appliance sales (in dollars) as the dependent variable and disposable personal income and new housing starts as the independent variables. The statistical tests of the model showed large t-values for both independent variables, along with a high r2 value. However, analysis of the residuals indicated that substantial autocorrelation was present.a. What are some of the possible causes of this autocorrelation?b. How does this autocorrelation affect the conclusions concerning the significance of the individual explanatory variables and the overall explanatory power of the regression model?c. Given that a person uses the model for forecasting future appliance sales, how does this autocorrelation affect the accuracy of these forecasts?d. What techniques might be used to remove this autocorrelation…
) In estimating the regression in the previous problem (#2), you are concerned that the t-statistics may be inflated because of serial correlation. You compute the DW statistic at 0.724 for the regression Based on the DW, what can you say about serial correlation between the residuals? Are they positively or negatively correlated? Or not correlated? Compute the sample correlation between the regression residuals from one period and those from the previous period. Perform a statistical test at the level to see if there is serial correlation. If you are using the table in the textbook, assume that the critical values of the DW statistic for 214 observations are about 0.11 higher than the critical values for 100 observations.
An econometrician suspects that the residuals of her model might be autocorrelated. Explain the steps involved in testing this theory using the Durbin–Watson (DW) test
In a regression analysis involving 25 observations, the following estimated regression equation was developed.ŷ = 10 – 18x1 + 3x2 + 14x3Also, the following standard errors and the sum of squares were obtained.Sb1 = 3 Sb1 = 6 Sb1 = 7SST = 4,800 SSE = 1,296If we are interested in testing for the significance of the relationship among the variables (i.e., significance of the model), the critical value of F at α = .05 is _____.
Suppose the following are the seasonal indices for the first three quarters of the year for a quarterly series: Quarter Seasonal Index Q1 73.8 Q2 86.1 Q3 109.2 Remember that the seasonal indices should average 100 so you should be able to infer the seasonal index for Q4. Furthermore, suppose that the estimated coeffcients from a regression of the deseasonalized series on Time are given below: Coefficients Intercept 2,291 Time 54.9 In general, what quarter is the busiest time of the year? (please just answer 1, 2, 3, or 4)
You have run a regression of monthly stock returns for Gym Place Holdings, a small play-set manufacturing company against the S&P 500 over the last 5 years. The results are summarized below: ReturnsGym Place = 0.0003 + 2.00 Returns S&P 500 R2 = 0.5, the standard error for the beta estimate is 0.5 If you know that this stock had a monthly Jensen’s alpha of 0.005 during the period of the regression. The 10-year U.S. treasury bond rate is 0.039, the German government Euro bond rate is 0.034 and Gym Place can borrow money at 0.06 (in Euros). The risk premium (Equity over risk free rate) over the last 10 years in European markets is only 0.04 but the historical risk premium over the last 75 years in the United States is 0.0453. Using Jensens alpha, What was the monthly risk free rate ? What was the annualized risk free rate during the last 5 years? Estimate a Euro cost of equity for Gym Place Holdings

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