Transcription of 89782 03 c03 p073-122 - Cengage Learning
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89782 03 c03 p073-122 - Cengage Learning
733 Multiple regression Analysis: EstimationIn Chapter 2, we learned how to use simple regression analysis to explain a dependentvariable,y, as a function of a single independent variable,x. The primary drawback inusing simple regression analysis for empirical work is that it is very difficult to drawceteris paribus conclusions about how x affects y: the key assumption, that allother factors affecting y are uncorrelated with x is often regression analysis is more amenable to ceteris paribus analysis because itallows us to explicitly control for many other factors that simultaneously affect the depen-dent variable.
Multiple regression analysis is also useful for generalizing functional relationships between variables. As an example, suppose family consumption (cons) is a quadratic func-tion of family income (inc):cons b 0 b 1
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