Hi, I'm estimating an already log-linearized model with maximum likelihood (ML).
The ML estimates for some of the parameters seem to be very very close to the initial points that I specify. Is that a sign that these parameters are not well identified given the data and therefore should be calibrated prior to estimation?
I also used mode_check in my estimation command. For most of the parameters, the estimate is at the trough of the parabola, but for some it isn't. Does this indicate that the program has found a local max rather than a global max? Should I move the initial parmater guesses towards the direction of the troughs?
In general, how do I make sure I obtain estimates with the global max? I don't get the same results when I start the program from different initial values. Should I be comparing the likelihood in each case? Is there any recipe that people follow to be more or less confident about their ML estimates?
Thanks for the help. Deeply appreciated.
otb