SAS Assignment observing food consumption patterns in an Engel Curve

For my regression I observed food consumption rates in dollars, plotted against income level as the explanatory variable. I used a measurement of income before taxes separated into 9 different brackets: <$15,000, <$30,000, <$40,000, <$50,000, <$70,000, <$100,000, <$150,000, <$200,000, and <$250,000. I ran a cross sectional regression to observe changes in food consumption due to increases in annual income. For a second regression, I included alcohol consumption in dollars to observe its effect on food consumption under the same income brackets.

 

In my first test, I found that each additional dollar of income will lead to a $0.04 dollar increase in food consumption. For my second model, I found that each additional dollar spent on alcohol consumption causes a $1.95 decrease in spending on food, holding the other variable (income) constant. My R squared statistics of .993 and .995 (respectively) suggests this regression, and its independent variables, hold a high strength of explanation for the dependent variable (food consumption). These findings align with our common assumptions about food, that it is a highly normal good.

 

Output information is presented below.

 

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