A tobit model is a type of censored regression model used to analyze data with a lower or upper limit, such as when the dependent variable is non-negative. In contrast, a hurdle model is designed to handle data with an excess of zeros or other specific values. While both models can be used to analyze data with a large number of zeros, the tobit model assumes that the zeros are part of the same underlying distribution as the non-zero values, whereas the hurdle model separates the analysis of zeros and non-zero values into two distinct stages.