In regression applications in which the dependent variable is a binary random variable, the choices of model include the linear probability model, the logit model and the probit model. Being nonlinear, the logit and probit models are more difficult to work with. However, the linear probability model also has some disadvantages.
What are the disadvantages of the linear probability model?