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This paper presents findings from a study of the experiences and outcomes of older and younger community college students. We developed a discrete-time hazard model using longitudinal transcript data on a cohort of first-time community college students in Florida to compare the impact of enrollment pathways (such as remediation) and enrollment milestones (such as attaining a certain number of credits) on educational outcomes of older students—those who enter college for the first time at age 25 or later—with those of traditional-age students. Results suggest that reaching milestones such as obtaining 20 credits or completing 50 percent of a program is a more important positive factor affecting graduation probabilities for younger students than it is for older students. We also found that although enrollment in remedial courses decreases the odds of graduating for all students, older students who enroll in remediation are less negatively affected than are younger ones who take remedial classes. [ABSTRACT FROM AUTHOR]

This study makes two main contributions to the applied econometrics literature. First, it shows how the all-important marginal effects for time on the market and probability of sale can be obtained from any hazard model. Second, it extends the generalization of the geometric due to Gómez-Déniz, E. 2010. "Another Generalization of the Geometric Distribution." Test 19: 399–415 to include covariates for use in the estimation of time on the market and probability of sale regressions in real estate, thus creating an entirely new hazard model based on probability of sale rather than time on the market. For the generalized geometric we develop expressions for the marginal effects (with approximate standard errors) for both the probability of sale and time on the market. This formulation allows the impact of changes in independent variables on both the probability of sale and time on the market to be determined from a single regression model. For comparison, we also obtain these two sets of marginal effects for the popular Weibull hazard model. The geometric, generalized geometric, and Weibull hazard models, along with two sets of marginal effects for each, are estimated using data on condominium listings in a metropolitan area in Florida. [ABSTRACT FROM AUTHOR]