Econometric Explain why it is


Explain why it is dangerous to judge the quality of a regressionmodel by maximizing R^2?

You are encouraged to use a hypothetical example in answeringthis question. (Your answer should be more than 2 sentenceslong).


R-squared is the percentage of the dependent variable variationthat the model explains. The value in your statistical output is anestimate of the population value that is based on your sample. Likeother estimates in inferential statistics, you want your R-squaredestimate to be close to the population value.

There are situations where the R2in your output is much higherthan the correct value for the entire population. Additionally,these conditions can cause other problems, such as misleadingcoefficients. Consequently, it ispossible to have anR-squared value that is too high even though that soundscounter-intuitive.

High R2 values are not always a problem. In fact, sometimes youcan legitimately expect very large values. For example, if you arestudying a physical process and have very precise and accuratemeasurements, it’s possible to obtain valid R-squared values in thehigh 90s.

On the other hand, human behavior inherently has much moreunexplainable variability, and this produces R2 values that areusually less than 50%. 90% is way too high in this context!

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