Chapter 13

Qualitative Dependent Variables

In This Chapter

arrow Modeling qualitative outcomes

arrow Estimating a linear probability model

arrow Revealing the limitations of the linear probability model

arrow Estimating and interpreting probit and logit models

What distinguishes a job applicant who gets hired from one who doesn’t? What influences whether an individual’s loan application gets approved or rejected? How does a commuter decide between using a car and using some alternative form of transportation to reach work? These questions all concern qualitative outcomes that either occur or do not occur. The outcomes are dichotomous (meaning only two outcomes are possible) and not continuous or normally distributed. For this reason, these models are also known as dummy dependent variable models. If you want to model qualitative outcomes of this nature and use regression analysis, you can use traditional ordinary least squares (OLS), but you’ll likely need special econometric techniques to properly model the outcome of interest.

In this chapter, I show you the econometric techniques most commonly used ...

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