below are EXCEL outputs for various estimated autoregressivemodels for Coca-Cola's real operating revenues (in billions ofdollars) from 1975 to 1998. From the data, we also know that thereal operating revenues for 1996, 1997, and 1998 are 11.7909,11.7757 and, 11.5537,respectively. AR(1) Model:
| Coefficients | StandardError | tStat | P-value |
| Intercept | 0.1802077 | 0.39797154 | 0.452815546 | 0.655325119 |
| XLag1 | 1.011222533 | 0.049685158 | 20.35260757 | 0.643735615 |
AR(2) Model:
| Coefficients | StandardError | tStat | P-value |
| Intercept | 0.30047473 | 0.4407641 | 0.681713257 | 0.503646149 |
| X Lag 1 | 1.17322186 | 0.234737881 | 4.998008229 | 7.98541E-05 |
| X Lag2 | -0.183028189 | 0.030716669 | -0.730020026 | 0.034283347 |
AR(3) Model:
| Coefficients | StandardError | tStat | 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:
