Your firm is attempting to learn the effectiveness of a newly developed television ad on its sales. To do this, it has randomly run the ad between 0 and 5 times during one week across a large number of television markets in the United States. It then recorded product sales for the following month for each market. To conduct the analysis, analysts at the firm have assumed the following data-generating process:

Salesi=α+βAdsi+Ui

Regressing Sales on Ads yields βˆ=350. The firm would like to use this number to project the change in Sales when increasing weekly television ads to 20.

According to these results, what is the expected change in Sales when Ads increase from 5 to 20?

Why should we be skeptical of our result from Part a?

What can you do to find an estimate of the effect of increasing Ads from 5 to 20 that is more credible?

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