Principles of Economics 2e
Principles of Economics 2e
2nd Edition
ISBN: 9781947172364
Author: Steven A. Greenlaw; David Shapiro
Publisher: OpenStax
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Chapter 20, Problem 31CTQ

As technological change makes us more sedentary and food costs increase, obesity is likely. What factors do you think may limit obesity?

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Suppose you are working as a manager of an organic grocery store and want to analyze how income affects grocery spending. In the dataset, grocery_spending measures the amount spent on groceries in dollars, and income represents individual income, also measured in dollars. The following regression results present estimates from two different specifications. reg grocery_spending income Source SS df MS Model Residual 20685432.5 29227282.9 1 20685432.5 9,998 2923.31295 Number of obs = F(1, 9998) Prob > F R-squared => 10,000 7076.02 0.0000 Total 49912715.4 9,999 4991.77071 Adj R-squared = Root MSE = 0.4144 54.068 grocery_sp~g Coefficient Std. err. t P>|t| [95% conf. interval] income _cons 0033984 .0000404 84.12 2113.24 1.144063 1847.14 0.000 0.000 .0033192 2110.998 .0034776 2115.483 ⚫ gen Inincome-In (income) .reg grocery_spending Inincome Source SS df MS Number of obs = 10,000 Model Residual 24748934.7 25163780.7 9,998 1 24748934.7 2516.88144 F(1, 9998) Prob > F R-squared = 9833.17 " =…
Both the level-level and level-log regression models presented above use the same number of observations. What does this suggest about the variables used in each model?
Calculate the R-squared value for the missing section. (Round totwo decimal places. You do not need to show your work.) Based on this answer, which model specification provides a better fit to the data? Why?    On the level-level model specification, what is the null hypothesiswe would like to reject? Briefly describe the null hypothesis in words.

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