Final answer:
The drawback of the linear probability model is not the presence of homoskedasticity, but rather its tendency towards heteroskedastic errors. The Ricker-Allee model offers an alternative approach to address this issue in sparse data series.
Step-by-step explanation:
The statement that a drawback of the linear probability model is the presence of homoskedasticity is false. In fact, one of the main limitations of the linear probability model is its tendency to produce heteroskedastic errors, not homoskedastic. This means that the variance of the errors changes across different levels of the independent variables, which violates one of the key assumptions of ordinary least squares regression. To address this issue, other models such as the Ricker-Allee model have been developed to better accommodate sparse series and varying detection probabilities.