For my bachelor thesis I predicted a multinomial logistic model and used it for predicting outcomes of football (soccer) games, and estimated the expected return when using this model. This gave me insights into the multinomial logit model as well as a lot of programming experience. So this might be a subject to write about again.

I am also very interested in estimation under non-response. The Heckman two-step estimator, the Särndal & Lundström estimator and GREG two-phase estimation are interesting topics, for example.

Another interesting topic would be to conduct a simulation study and examine the properties of the estimated parameters using different methods of estimating them. Usually we estimate parameters of a model by choosing parameter estimates which minimizes the squared distances. An interesting topic is how well methods like minimization of MAD and/or the absolute values of the cubed distances (and maybe some other methods of estimating the parameters) performs. But I guess this have been studied extensively already, and simulation studies feels so 1980.

Please suggest topics if you have any ideas