Activity I – The data in the file attached contains information on your firm's sales per capita, advertising expenditure per capita, and average local income.Regress sales per capita on advertising expenditure per capita, controlling for local income as an interval variable, where intervals are <$35,000, $35,000–$44,999, $45,000–$54,999, and $55,000+, and <$35,000 is the base group.For the remainder of the question, assume the data-generating process isSalesperCapitai = α + β1AdExpperCapitai + β2Inc35-45i + β3Inc45-55i + β4Inc55i + Ui and that all other necessary assumptions toward establishing causality and performing inference hold.
- Interpret the coefficients for the income intervals from your regression.
- According to this regression, what is the effect on sales per capita when average local income increases from $35,000−$44,999 to $55,000+?
Activity III – Suppose you have data on 200 firms, and half advertise on Google. If the advertising firms had higher sales than nonadvertising firms before they started advertising on Google, does this fact impact your ability to measure the effect of Google advertising on sales using these data?
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