# Question: Inventory The following regression model forecasts inventory levels at Wal Mart

Inventory The following regression model forecasts inventory levels at Wal-Mart (in millions of dollars). The predictors are two lags of the aggregate consumer credit debt in the United States (in billions of dollars). Both data series are quarterly from 1993 through 2011 1n = 1282. The equation of the multiple regression is assumed to be

Estimated Inventory t = b0 + b1 Debt t -1 + b2 Debt t -2

(a) Find the least squares estimates and summarize the estimated equation. What is the interpretation of the estimated intercept and slopes?

(b) The regression uses two lags of Debt. Would adding a third or fourth lag improve the ft of this model?

(c) For forecasting, why it is important that the model does not use Debt t as a predictor?

(d) Use color codes or different plotting symbols to distinguish the quarter 11, 2, 3, or 42 in the timeplot of the residuals. Do the residuals from the estimated equation differ from quarter to

quarter? That is, can you distinguish the residuals from certain quarters?

Estimated Inventory t = b0 + b1 Debt t -1 + b2 Debt t -2

(a) Find the least squares estimates and summarize the estimated equation. What is the interpretation of the estimated intercept and slopes?

(b) The regression uses two lags of Debt. Would adding a third or fourth lag improve the ft of this model?

(c) For forecasting, why it is important that the model does not use Debt t as a predictor?

(d) Use color codes or different plotting symbols to distinguish the quarter 11, 2, 3, or 42 in the timeplot of the residuals. Do the residuals from the estimated equation differ from quarter to

quarter? That is, can you distinguish the residuals from certain quarters?

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