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The Following Table Shows the Annual Revenues (In Millions of Dollars)of

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The following table shows the annual revenues (in millions of dollars)of a pharmaceutical company over the period 1990-2011. The following table shows the annual revenues (in millions of dollars)of a pharmaceutical company over the period 1990-2011. The autoregressive models of order 1 and 2,y<sub>t</sub> = β<sub>0</sub> + β<sub>1</sub>y<sub>t - </sub><sub>1</sub> + ε<sub>t</sub>,and y<sub>t</sub> = β<sub>0</sub> + β<sub>1</sub>y<sub>t - </sub><sub>1</sub> + β<sub>2</sub>y<sub>t - 2</sub> + ε<sub>t</sub>,were applied on the time series to make revenue forecasts.The relevant parts of Excel regression outputs are given below. Model AR(1): Model AR(2): When for AR(1),H<sub>0</sub>: β<sub>0</sub> = 0 is tested against H<sub>A</sub>: β<sub>0</sub> ≠ 0,the p-value of this t test shown by Excel output is 0.9590.This could suggest that the model y<sub>t</sub> = β<sub>1</sub>y<sub>t</sub><sub>-1 </sub>+ ε<sub>t</sub> might be an alternative to the AR(1)model y<sub>t</sub> = β<sub>0</sub> + β<sub>1</sub>y<sub>t-1</sub> + ε<sub>t</sub>.Excel partial output for this simplified model is as follows: Find the revenue forecast for 2012 through the use of y<sub>t</sub> = β<sub>1</sub>y<sub>t-1</sub> + ε<sub>t</sub>. The autoregressive models of order 1 and 2,yt = β0 + β1yt - 1 + εt,and yt = β0 + β1yt - 1 + β2yt - 2 + εt,were applied on the time series to make revenue forecasts.The relevant parts of Excel regression outputs are given below.
Model AR(1): The following table shows the annual revenues (in millions of dollars)of a pharmaceutical company over the period 1990-2011. The autoregressive models of order 1 and 2,y<sub>t</sub> = β<sub>0</sub> + β<sub>1</sub>y<sub>t - </sub><sub>1</sub> + ε<sub>t</sub>,and y<sub>t</sub> = β<sub>0</sub> + β<sub>1</sub>y<sub>t - </sub><sub>1</sub> + β<sub>2</sub>y<sub>t - 2</sub> + ε<sub>t</sub>,were applied on the time series to make revenue forecasts.The relevant parts of Excel regression outputs are given below. Model AR(1): Model AR(2): When for AR(1),H<sub>0</sub>: β<sub>0</sub> = 0 is tested against H<sub>A</sub>: β<sub>0</sub> ≠ 0,the p-value of this t test shown by Excel output is 0.9590.This could suggest that the model y<sub>t</sub> = β<sub>1</sub>y<sub>t</sub><sub>-1 </sub>+ ε<sub>t</sub> might be an alternative to the AR(1)model y<sub>t</sub> = β<sub>0</sub> + β<sub>1</sub>y<sub>t-1</sub> + ε<sub>t</sub>.Excel partial output for this simplified model is as follows: Find the revenue forecast for 2012 through the use of y<sub>t</sub> = β<sub>1</sub>y<sub>t-1</sub> + ε<sub>t</sub>. The following table shows the annual revenues (in millions of dollars)of a pharmaceutical company over the period 1990-2011. The autoregressive models of order 1 and 2,y<sub>t</sub> = β<sub>0</sub> + β<sub>1</sub>y<sub>t - </sub><sub>1</sub> + ε<sub>t</sub>,and y<sub>t</sub> = β<sub>0</sub> + β<sub>1</sub>y<sub>t - </sub><sub>1</sub> + β<sub>2</sub>y<sub>t - 2</sub> + ε<sub>t</sub>,were applied on the time series to make revenue forecasts.The relevant parts of Excel regression outputs are given below. Model AR(1): Model AR(2): When for AR(1),H<sub>0</sub>: β<sub>0</sub> = 0 is tested against H<sub>A</sub>: β<sub>0</sub> ≠ 0,the p-value of this t test shown by Excel output is 0.9590.This could suggest that the model y<sub>t</sub> = β<sub>1</sub>y<sub>t</sub><sub>-1 </sub>+ ε<sub>t</sub> might be an alternative to the AR(1)model y<sub>t</sub> = β<sub>0</sub> + β<sub>1</sub>y<sub>t-1</sub> + ε<sub>t</sub>.Excel partial output for this simplified model is as follows: Find the revenue forecast for 2012 through the use of y<sub>t</sub> = β<sub>1</sub>y<sub>t-1</sub> + ε<sub>t</sub>. Model AR(2): The following table shows the annual revenues (in millions of dollars)of a pharmaceutical company over the period 1990-2011. The autoregressive models of order 1 and 2,y<sub>t</sub> = β<sub>0</sub> + β<sub>1</sub>y<sub>t - </sub><sub>1</sub> + ε<sub>t</sub>,and y<sub>t</sub> = β<sub>0</sub> + β<sub>1</sub>y<sub>t - </sub><sub>1</sub> + β<sub>2</sub>y<sub>t - 2</sub> + ε<sub>t</sub>,were applied on the time series to make revenue forecasts.The relevant parts of Excel regression outputs are given below. Model AR(1): Model AR(2): When for AR(1),H<sub>0</sub>: β<sub>0</sub> = 0 is tested against H<sub>A</sub>: β<sub>0</sub> ≠ 0,the p-value of this t test shown by Excel output is 0.9590.This could suggest that the model y<sub>t</sub> = β<sub>1</sub>y<sub>t</sub><sub>-1 </sub>+ ε<sub>t</sub> might be an alternative to the AR(1)model y<sub>t</sub> = β<sub>0</sub> + β<sub>1</sub>y<sub>t-1</sub> + ε<sub>t</sub>.Excel partial output for this simplified model is as follows: Find the revenue forecast for 2012 through the use of y<sub>t</sub> = β<sub>1</sub>y<sub>t-1</sub> + ε<sub>t</sub>. The following table shows the annual revenues (in millions of dollars)of a pharmaceutical company over the period 1990-2011. The autoregressive models of order 1 and 2,y<sub>t</sub> = β<sub>0</sub> + β<sub>1</sub>y<sub>t - </sub><sub>1</sub> + ε<sub>t</sub>,and y<sub>t</sub> = β<sub>0</sub> + β<sub>1</sub>y<sub>t - </sub><sub>1</sub> + β<sub>2</sub>y<sub>t - 2</sub> + ε<sub>t</sub>,were applied on the time series to make revenue forecasts.The relevant parts of Excel regression outputs are given below. Model AR(1): Model AR(2): When for AR(1),H<sub>0</sub>: β<sub>0</sub> = 0 is tested against H<sub>A</sub>: β<sub>0</sub> ≠ 0,the p-value of this t test shown by Excel output is 0.9590.This could suggest that the model y<sub>t</sub> = β<sub>1</sub>y<sub>t</sub><sub>-1 </sub>+ ε<sub>t</sub> might be an alternative to the AR(1)model y<sub>t</sub> = β<sub>0</sub> + β<sub>1</sub>y<sub>t-1</sub> + ε<sub>t</sub>.Excel partial output for this simplified model is as follows: Find the revenue forecast for 2012 through the use of y<sub>t</sub> = β<sub>1</sub>y<sub>t-1</sub> + ε<sub>t</sub>. When for AR(1),H0: β0 = 0 is tested against HA: β0 ≠ 0,the p-value of this t test shown by Excel output is 0.9590.This could suggest that the model yt = β1yt-1 + εt might be an alternative to the AR(1)model yt = β0 + β1yt-1 + εt.Excel partial output for this simplified model is as follows: The following table shows the annual revenues (in millions of dollars)of a pharmaceutical company over the period 1990-2011. The autoregressive models of order 1 and 2,y<sub>t</sub> = β<sub>0</sub> + β<sub>1</sub>y<sub>t - </sub><sub>1</sub> + ε<sub>t</sub>,and y<sub>t</sub> = β<sub>0</sub> + β<sub>1</sub>y<sub>t - </sub><sub>1</sub> + β<sub>2</sub>y<sub>t - 2</sub> + ε<sub>t</sub>,were applied on the time series to make revenue forecasts.The relevant parts of Excel regression outputs are given below. Model AR(1): Model AR(2): When for AR(1),H<sub>0</sub>: β<sub>0</sub> = 0 is tested against H<sub>A</sub>: β<sub>0</sub> ≠ 0,the p-value of this t test shown by Excel output is 0.9590.This could suggest that the model y<sub>t</sub> = β<sub>1</sub>y<sub>t</sub><sub>-1 </sub>+ ε<sub>t</sub> might be an alternative to the AR(1)model y<sub>t</sub> = β<sub>0</sub> + β<sub>1</sub>y<sub>t-1</sub> + ε<sub>t</sub>.Excel partial output for this simplified model is as follows: Find the revenue forecast for 2012 through the use of y<sub>t</sub> = β<sub>1</sub>y<sub>t-1</sub> + ε<sub>t</sub>. The following table shows the annual revenues (in millions of dollars)of a pharmaceutical company over the period 1990-2011. The autoregressive models of order 1 and 2,y<sub>t</sub> = β<sub>0</sub> + β<sub>1</sub>y<sub>t - </sub><sub>1</sub> + ε<sub>t</sub>,and y<sub>t</sub> = β<sub>0</sub> + β<sub>1</sub>y<sub>t - </sub><sub>1</sub> + β<sub>2</sub>y<sub>t - 2</sub> + ε<sub>t</sub>,were applied on the time series to make revenue forecasts.The relevant parts of Excel regression outputs are given below. Model AR(1): Model AR(2): When for AR(1),H<sub>0</sub>: β<sub>0</sub> = 0 is tested against H<sub>A</sub>: β<sub>0</sub> ≠ 0,the p-value of this t test shown by Excel output is 0.9590.This could suggest that the model y<sub>t</sub> = β<sub>1</sub>y<sub>t</sub><sub>-1 </sub>+ ε<sub>t</sub> might be an alternative to the AR(1)model y<sub>t</sub> = β<sub>0</sub> + β<sub>1</sub>y<sub>t-1</sub> + ε<sub>t</sub>.Excel partial output for this simplified model is as follows: Find the revenue forecast for 2012 through the use of y<sub>t</sub> = β<sub>1</sub>y<sub>t-1</sub> + ε<sub>t</sub>. Find the revenue forecast for 2012 through the use of yt = β1yt-1 + εt.

Definitions:

Accounts Receivable Turnover

A financial ratio indicating how efficiently a company collects cash from credit sales by measuring the number of times receivables are collected over a period.

Inventory Turnover

An index that reveals the number of times a business's stock is sold and restocked during a specific period, showcasing how efficiently inventory is managed.

Total Current Assets

Assets of a company that are expected to be used or converted to cash within one year.

Debt/Equity Ratio

Determination of a firm's borrowing dependency, achieved by dividing its liabilities by its shareholder's equity.

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