Given below are EXCEL outputs for various estimated autoregressive models for Co

Question

Given 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.

Given 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 0.397971540452815546 0.655325119 XLagl 1.011222533 0.04968515820.35260757 0.643735615 AR(2) Model: Coefficients Standard Error t Stat P-value Intercept 0.30047473 0.440764100.681713257 0.503646149 X Lag 1117322186 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 0.5144372570608515972 0.550890271 XLagl 1.173719587 0.246490594 4.761721601 0.000180926 XLag2 -0.069378567 0373086508 -0.185958391 0.854678245 XLag3 -0.122123515 0.282031297-0.433014053 0.670448392 Referring to Table 16-4 and using a 5% level of significance, what is the model that uses the most lag variables? AR(1) AR(2) AR(3) Any of the above.

Explanation / Answer

In statistics and econometrics, a distributed lag model is a model for time series data in which a regression equation is used to predict current values of a dependentvariable based on both the current values of an explanatory variable and thelagged (past period) values of this explanatory variable.

AR(3) uses the most lag variables.

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