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E-views - Essay Example

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Problem 1 The model to be estimated is: - (1) Where the variables are defined as follows: Table 1:Variable definitions Variable Definition Y Monthly manhours needed to operate an establishment X1 Average Daily occupation X2 Monthly average number of check ins X3 Weekly hours of service desk operation X4 Common use area (in square feet) X5 Number of building wings X6 Operational berthing capacity X7 Number of rooms The results of running the regression specified in equation 1 are presented in table 2 (Eviews output) below: Table 2: Results Dependent Variable: Y Method: Least Squares Date: 03/20/12 Time: 13:41 Sample: 1 25 Included observations: 25 Coefficient Std…
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Download file to see previous pages dependent var 1946.249 S.E. of regression 455.4699     Akaike info criterion 15.33487 Sum squared resid 3526698.     Schwarz criterion 15.72491 Log likelihood -183.6859     Hannan-Quinn criter. 15.44305 F-statistic 60.17375     Durbin-Watson stat 1.916498 Prob(F-statistic) 0.000000 (a) The estimated equation is: Y = 148.220572044 - 1.28739451915*X1 + 1.80962162969*X2 + 0.59039598443*X3 - 21.4816857405*X4 + 5.61940285601*X5 - 14.51467253*X6 + 29.3602583452*X7 The interpretation of the estimated coefficients is provided below: Table 3: Coefficient values and their interpretation Coefficient Value Interpretation Coefficient 1 148.2206 This is the intercept. ...
ase in the manhour requirement by approximately 0.60 hours per week Coefficient 5 -21.4817 for an increase of the common use area by an additional square feet will imply a reduction of the manhour requirement by 21 hours per month Coefficient 6 5.619403 If the number of building wings increases by one, the additional monthly manhour requirement rises by 5.61 Coefficient 7 -14.5147 for an increase of operational berthing capacity by an additional unit, the monthly manhour requirement falls by 14.51 Coefficient 8 29.36026 For every additional number of rooms, approximately 29.4 additional manhours per month become necessary (b) Testing for significances Here, n=25 and we test at the 95% level (0.05). The test is two sided. For these specifications, the critical value: . From the 4th column of table 2 we see that only the coefficients of X2, X4, X6 and X7 exceed the critical value (in absolute terms). Thus, these are the only variables that are found to be significant, i.e., the coefficients are statistically different from zero. It can be checked from the column of probabilities it is only these coefficients that have p-values less than 0.05. Therefore, the conclusion is that only the monthly number of check ins, common use area, operational berthing capacity and number of rooms have statistically significant effects on the predicted variable, the required manhours to run the establishment. Problem 2 The test of joint significance is an F test of the null hypothesis that all coefficients are equal to zero, i.e., the parameters are jointly insignificant. In Eviews this is equivalent to using the Wald test for testing the restriction: The 5% critical F-statistic value for one restriction and 17 degrees of freedom (n=25, k=8) is 4.451. Observe from table 2 that the computed ...Download file to see next pagesRead More
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