I'm running a regression which has life satisfaction (measured in a 1-10 scale) as a dependent variable and a relatively big set of consumption variables (amount spent on amusement, cultural good, music-related goods, etc) as the regressors. Including the controls (demographics, education, etc.), I have almost 50 independent variables. I thought about using an ordered probit model, but I suspect that the parallel trends assumption is violated. Therefore, I want to use the partial proportional odds model, which uses a different equation for every category of the dependent variable *only* when the IV violates the parallel lines assumption. For this purpose, I used the gologit2 command with the autofit option. However, after 7 hours runnnig, STATA is still processing the regression. This is very unpractical because I have many other models that I have to run and I can't spend a day in each one. Therefore, I was wondering if there is a way to make it faster, or an alternative command that fits with my objective. If there is nothing to do, do you think it would be a good idea to run the regression in an Amazon's EC2 cloud computer?