In: Advanced Math
below are EXCEL outputs for various estimated autoregressive models for Coca-Cola's real operating revenues (in billions of dollars) from 1975 to 1998. From the data, we also know that the real operating revenues for 1996, 1997, and 1998 are 11.7909, 11.7757 and, 11.5537, respectively. AR(1) Model:
Coefficients | Standard Error | t Stat | P-value | |
Intercept | 0.1802077 | 0.39797154 | 0.452815546 | 0.655325119 |
XLag1 | 1.011222533 | 0.049685158 | 20.35260757 | 0.643735615 |
AR(2) Model:
Coefficients | Standard Error | t Stat | P-value | |
Intercept | 0.30047473 | 0.4407641 | 0.681713257 | 0.503646149 |
X Lag 1 | 1.17322186 | 0.234737881 | 4.998008229 | 7.98541E-05 |
X Lag 2 | -0.183028189 | 0.030716669 | -0.730020026 | 0.034283347 |
AR(3) Model:
Coefficients | Standard Error | t Stat | P-value | |
Intercept | 0.313043288 | 0.514437257 | 0.608515972 | 0.550890271 |
XLag1 | 1.173719587 | 0.246490594 | 4.761721601 | 0.000180926 |
XLag2 | -0.069378567 | 0.373086508 | -0.185958391 | 0.004678245 |
XLag3 | -0.122123515 | 0.282031297 | -0.433014053 | 0.30448392 |
Referring to Table 16-4 and using a 5% level of significance, what is the model that uses the most lag variables?
Question 7 options:
linear |
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AR(3) |
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AR(2) |
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AR(1) |