Ordinary least squares is used to estimate a linear relationship between a firm\

Question

Ordinary least squares is used to estimate a linear relationship between a firm's quantity sold per month and its total promotional expenditures, and the slope of the linear function is found to be positive and significantly different from zero. Assuming that all other variables, including product price, were constant during the period covered by the data set, this result implies that

the firm should spend more on promotional expenditures.

the firm should spend less on promotional expenditures.

promotional expenditures influence demand.

promotional expenditures have no influence on demand.

1 points   

Question 24

Time-series forecasting models:                                                                                    

are useful whenever changes occur rapidly and wildly

are more effective in making long-run forecasts than short-run forecasts

are based solely on historical observations of the values of the variable being forecasted

attempt to explain the underlying causal relationships which produce the observed outcome

none of the above

1 points   

Question 25

The forecasting technique which attempts to forecast short-run changes and makes use of economic indicators known as leading, coincident or lagging indicators is known as:

econometric technique

time-series forecasting

opinion polling

barometric methods

judgment forecasting

1 points   

Question 26

Variations in a time-series forecast can be caused by:                                                  

cyclical variations                 

secular trends

seasonal effects

all of the above

Please do not just guess , !!! Thanks

the firm should spend more on promotional expenditures.

the firm should spend less on promotional expenditures.

promotional expenditures influence demand.

promotional expenditures have no influence on demand.

Explanation / Answer

1. promotional expenditures influence demand.

2. are based solely on historical observations of the values of the variable being forecasted

3. barometric methods

4. all of the above

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